Eccm in radar

MODELLING RADAR-ECCM
A SYSTEM APPROACH
AK Subramanian

MODELLING RADAR-ECCM
A SYSTEM APPROACH
AK Subramanian
Defence Research & Development Organisation
Ministry of Defence
New Delhi – 110 011
2003

DRDO MONOGRAPH SERIES
MODELLING RADAR-ECCM: A SYSTEM APPROACH
AK Subramanian
Series Editors
Editor-in-Chief Editors
Dr Mohinder Singh Dr JP Singh, A Saravanan
Coordinator
Ashok Kumar
Asst. Editors Editorial Assts. Cover Design
Ramesh Chander AK Sen, RK Saxena Anjan Das
Sanjay Kumar Kumar Amar Nath
Production
Printing Marketing
JV Ramakrishna RK Dua
SK Tyagi Rajpal Singh
Cataloguing in Publication
Subramanian, A.K.
Modelling radar-ECCM: a system approach.
DRDO monograph series.
Includes index and bibliography.
ISBN 81-86514-12-0
1. Radar 2. ECCM I. Title (Series)
623.623
© 2003, Defence Scientific Information & Documentation Centre (DESIDOC), Defence
R&D Organisation, Delhi-110 054.
All rights reserved. Except as permitted under the Indian Copyright Act 1957, no
part of this publication may be reproduced, distributed or transmitted, stored in a
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The views expressed in the book are those of the author only. The editors or publisher
do not assume responsibility for the statements/opinions expressed by the author.
Printed and published by Director, DESIDOC, Metcalfe House, Delhi-110 054.

Dedicated
to
Gita Subramanian
for
the inspiration, help and support

CONTENTS
Preface xi
Acknowledgement xiii
CHAPTER 1
INTRODUCTION 1
1.1 Importance of ECM 1
1.2 Background 2
1.3 Basic Considerations 2
1.3.1 Jamming Interference 3
1.4 ECM-ECCM Matrix Dynamics 4
1.4.1 ECCM Efficacy–The Difficulty 5
1.4.2 Survival 5
1.4.3 Judging Efficacy of an ECCM Element 6
1.5 Assessment of the State-of-the-Art 6
CHAPTER 2
MODERN RADAR DESIGN & ITS DEPLOYMENT
ENVIRONMENT 9
2.1 Introduction 9
2.2 Radar Performance 10
2.2.1 Two Representative Radar Models 10
2.2.1.1 Low Flying Detection Model 10
2.2.1.2 Land Clutter Model for Radar Design 11
2.3 Command, Control, Communication & Intelligence 13
2.4 ECCM Modelling 14
2.4.1 Radar Systems 14
2.4.2 Communication Systems 15
2.5 Mathematical Analysis 15
2.6 Simulation 15
2.7 The EW Flywheel 16
Reference

(viii)
CHAPTER 3
ECCM EVALUATION–SOME MODELS 19
3.1 Introduction 19
3.2 ECCM Improvement Factor 19
3.3 Functional Models 20
3.4 Response to Specific ECM 21
3.5 Deployment Models 22
3.6 Weapon System Efficacy 22
3.7 Game Theory Model 22
3.7.1 Case Study 1 23
3.7.2 Case Study 2 23
References
CHAPTER 4
MODELLING FOR ELECTRONIC CONFLICT:
THE BURNTHROUGH EQUATION MODEL 27
4.1 Background 27
4.2.1 Burnthrough Range 29
4.2.2 Escort Jammer 29
4.2.3 On-board Jammer 30
4.2.4 Repeater Jammer 30
4.3 Comments on the Burnthrough Range Equation 31
4.4 A Relook at the Burnthrough Range Relationship 32
4.4.1 Dynamic Radar Range Equation 33
4.5 Search Radar Modelling for ECCM 34
4.5.1 Functions of Radar Variables 34
4.5.2 Antenna Function 36
4.5.3 Jammer Function 37
4.6 Low Flying Target Detection Model 38
References
CHAPTER 5
LOW PROBABILITY OF INTERCEPT SEARCH
RADAR MODEL 39
5.1 Radar Detection & LPI 39
5.1.1 Detection 40

(ix)
5.1.2 Search Antenna 40
5.2 Intercept Receiver 41
5.3 Interface Between Radar & Interceptor 42
5.3.1 Effect of Receiver Aperture 42
5.3.2 Conflicts 42
5.3.3 LPI Modulation Scheme 43
5.3.4 Interceptor Receiver Bandwidth 43
5.4 LPI–ECCM 43
5.5 LPI–ECCM Radar Models 44
5.5.1 Radar vs Interceptor 44
References
CHAPTER 6
ECCM IN MULTIFUNCTION RADAR 49
6.1 Introduction 49
6.2 MFR ECCM: The RF Chain 50
6.3 MFR Antenna ECCM 50
6.4 MFR Transmitter ECCM 53
6.5 MFR Receiver ECCM 54
6.6 Resistance to Anti Radiation Missile 54
6.7 ECCM Evaluation 55
6.8 Comment 56
References
CHAPTER 7
RADAR ECCM MODEL THROUGH PETRI NETS 59
7.1 Conflicts 59
7.2 Petri Net 59
7.3 Extended & Timed Petri Nets 60
7.4 ECCM Modelling Through Petri Nets 60
7.5 Concluding Remarks 67
References
CHAPTER 8
GAME THEORY MODEL APPROACH TO RADAR ECCM
EVALUATION 69
8.1 Applications to ECCM Evaluation 70
8.2 Point-Defence Surface Radar 76

(x)
8.3 Conclusion 79
References
CHAPTER 9
KNOWLEDGE-BASED INFERENCE FOR RADAR ECCM 83
9.1 ECCM Decisions 83
9.2 Acquisition of ECCM Knowledge Base 86
9.3 Knowledge-based Classification 86
9.3.1 Handcrafting 88
9.4 Knowledge-based Simulation & Evaluation 90
References
CHAPTER 10
CONCLUSION 93
Index 95

PREFACE
Conflict situations are part of human life. What this
monograph wishes to deal with is about the area of conflict that
World Wars have brought about; that of the electronic encounters,
often fraught with far-reaching consequences. History has many
tales to tell, from the advent of World Wars, Egypt-Israeli conflicts,
Lebanon-Syria-Falkland encounters to the repeated encounters in
Iraq of the present times.
That the electronic battlefield’s armour is ‘Technology’ is
well understood. However, its application, results and evaluation
are mired in controversy, deception and secrecy–to become
ultimately justifiable and be synonymous with country’s honour at
the theatre of war.
It is the intention of this monograph to attempt an analysis
on one aspect of the electronic warfare–the counter
countermeasure of a radar sensor during an electronic conflict.
Finally, to the broad question of peace time simulation initiatives
so that we are all prepared to prevent the inevitable reaction under
duress.
Bangalore AK Subramanian
Date: Dec 6, 2003

ACKNOWLEDGEMENT
Grateful thanks and appreciation to Stephen L. Johnston,
USA, and with respectful remembrance of the Late Dr John Clarke,
UK, for the association, debate and research material and for
fostering an abiding interest in me on this subject of Radar.
AK Subramanian

CHAPTER 1
INTRODUCTION
1.1 IMPORTANCE OF ECM
The importance of Electronic Countermeasure (ECM) and
Electronic Counter Countermeasure (ECCM) in strategic and
tactical electronic warfare is not overstated. The ultimate survival
of any electronic system today is measured in terms of its
operational efficiency and survivability under adverse
electromagnetic environment. Defence radar and communication
networks are made vulnerable under such heavy and concentrated
attack. Apart from the conventional ECM attack delivered through
aerial and ground resources, a nuclear strike has its own
formidable component of Electromagnetic Pulse (EMP) which can
paralyse the entire chain of electronic sensors and associated
communication channels. A new dimension in the present era is
the added threat of the cyber warfare.
FigurFigurFigurFigurFigure1.1. Electre1.1. Electre1.1. Electre1.1. Electre1.1. Electronic waronic waronic waronic waronic warfarfarfarfarfareeeee
Signal Intelligence
(SIGINT)
COMMINT ELINT
Electronic
Countermeasures
Tactical
Intelligence
Electronic
Support
Measures
Electronic
Counter
Countermeasures
Stand-Off Jamming (SOJ)
Self-Protection Jamming (SPJ)
Escort Jamming
Repeaters, Spoof & Decoy
Detection Sensors
&
Communication
Strategic Plan
-9

Modelling Radar-ECCM: A System Approach
2
1.2 BACKGROUND
Considering its effective usage since World War II, it is not
surprising that the art of Electronic Warfare has gone through a
sea change over the last century. The real assessment of one’s
might as well as weakness in this area, is unfortunately proved
only during a major conflict. Modern examples have all been well
documented: those of the conflicts in Lebanon, Golan Heights,
Falklands, and the latest in the Gulf region. Whichever be the
theatre of war in future, it is amply clear that the initial strike
would be on the vital electronic defences of a country, be it the
missile complex, communication network, major air-defence
installation or the central and field headquarters.
The concept of a country’s boundary, guarded by its natural
geographical features, stays only as an historical fact these days.
Thanks to the modern technology, weapon development and
delivery systems, no nation needs to invade another territory to
start a war. Physical occupation may come later, but the initial
threat and thrust can be delivered from a safe distance. It is
presumed that the United States of America covertly supported
bombing of Iraqi Nuclear Facility by Israeli fighter planes. American
Warships positioned in the Mediterranean, guided the Israeli
fighters as well as provided facilities for the mid-air refuelling of its
aircraft. The Falkland War and the Gulf War had strong support of
satellite surveillance.
Further, even when delineated, the boundaries of a country
have a way of expanding due to economic and political reasons.
The USSR, when it existed, had its own ring of satellite countries
and the Warsaw Pact to protect its air space and the seas.
America’s reach was even wider and farther from its own country.
In India, due to the exploration of natural resources from the sea,
the naval complement of our defence effort extends our concern on
air-defence, even farther from the existing land boundaries. All in
all, the subject of air-defence rules the world as a modern dynamic
entity, precariously balanced and vulnerable to changes.
1.3 BASIC CONSIDERATIONS
Radar and communication systems have gone through a
sea change in the last three decades. Some of the old definitions
applied to the ECM-ECCM effectiveness have proved to be
inadequate.

Introduction
3
1.3.1 Jamming Interference
Jamming interference is mostly added in a nonlinear
fashion to the signal input of a radar sensor. Broadly, it can be
classified as one of the continuous noise, random pulse noise, or
synchronized pulse noise. The effects of jamming on radar are seen
in several ways. There is reduction in the Probability of Detection
Pd
, increase in the Probability of False Alarm Pfa
, poor accuracy in
tracking a target, poor resolution among targets, and a general
receiver saturation leading to non-linear processing. All of these
contribute to the degradation of the radar performance and
threaten its survivability.
Jamming effects are studied in terms of their spatial,
spectral, and temporal characteristics as they victimise different
blocks of the radar system. During jamming, a typical search radar
system suffers a loss in Pd
for a given Pfa
or it exhibits increased
false alarm rate while trying to maintain the same Pd
. In tracking
radars, the jammer’s intentions would be to increase the
probability of track interruption and or increase the track errors.
In guidance radars, the jammer would try to deny the guidance of
the weapon, both in terms of communication and the guidance
radar parameters.
Radars have now become multifunctional and adaptive
(Fig. 1.2). In the operating environment of a multifunctional radar, the
study of the ECM effects becomes more complex. Such a radar
FigurFigurFigurFigurFigure 1.2. Multifunctional radar capabilitye 1.2. Multifunctional radar capabilitye 1.2. Multifunctional radar capabilitye 1.2. Multifunctional radar capabilitye 1.2. Multifunctional radar capability
SEARCH TRACK GUIDANCE
MULTIFUNCTION
RADAR WITH
ADAPTIVE
CAPABILITIES

4
carries out a variety of tasks, from the initial detection of a target
to its final engagement by a guided weapon. A number of radar
parameters hence become vulnerable to the jamming threat than if
the radar had operated on a single function continuously. It is also
to be noticed that the multifunctional radar replaces the space
diversity in an air-defence complex, which would have been
available, if separate radars had been fielded to accomplish the
varied tasks of detection, tracking, and guidance.
Communication networks incorporate more and more
digital sophistication in modulation and have frequency, packet
switching facilities, error detection codes and secrecy.
Communication links relaying important data among sensors are
equally vulnerable to jamming effects. Among netted radars and in
radars relaying guidance commands, the survival of the
communication network is crucial to the effectiveness of the
air-defence complex. Some basic differences in the electronic
warfare (EW) between radar and communication network is
illustrated below (Fig. 1.3).
1.4 ECM-ECCM MATRIX DYNAMICS
The format of interaction between the countermeasure and
the counter-countermeasure is a variable by the very nature of a
conflict. To be effective, each one needs an element of surprise and
doses of deception. In practice, the turnaround time to field a new
ECM system is much shorter than that required for an appropriate
FigurFigurFigurFigurFigure 1.3.e 1.3.e 1.3.e 1.3.e 1.3. Some basic difSome basic difSome basic difSome basic difSome basic differferferferferences between radar and communicationences between radar and communicationences between radar and communicationences between radar and communicationences between radar and communication
network under electrnetwork under electrnetwork under electrnetwork under electrnetwork under electronic waronic waronic waronic waronic warfarfarfarfarfare.e.e.e.e.
COMMUNICATIONRADAR
EW
• Transmitter and receiver • Transmitter and receiver
usually co-located at different locations
• Two-way range for • One-way range for
transmission and reception transmission and reception
• Transmitter coding • Encryption for security
• Easier to spoof • More difficult

Introduction
5
ECCM response. What is more, new ECCM features cannot be
easily handled as add-on feature in a system already designed and
fielded. Therefore, the need to consider all the present and future
threats of ECM is a must before a solution is presented on the
required ECCM front. Building adequate adaptivity to the
electronic design is presently the best answer to the evolving
dynamics of ECM vs ECCM.
1.4.1 ECCM Efficacy–The Difficulty
The question “How good is an ECCM against a given ECM
threat?” or its converse has been engaging the attention of the
defence electronic community for many decades. In the World
War II era, the answer was mostly qualitative but it met their
requirements, as systems were essentially simple. Given the
complexities and diverse functions of present day defence
preparedness, a qualitative measure is no longer adequate.
All systems are designed on a cost-performance criterion. As such,
over-designing cannot be resorted to but must be constantly
challenged on cost-effective basis. Each ECCM function added to a
major system has to be weighed against performance vs cost, time
for introduction, compatibility with the existing functions of the
system and finally, its longevity in the ECM-ECCM conflict chain.
Further, each ECCM element has its own share of compromise on
the normal performance of the radar/communication equipment.
It is meant for survival purposes, and thus, should be judiciously
introduced. Some ECCM measures in tandem are not mutually
compatible. At this stage, the subject becomes difficult to track,
especially when one examines a case like the multifunctional radar
(MFR), which combines target search, identification, designation,
tracking, and finally guides the missiles towards it!
1.4.2 Survival
The survival of a military electronic complex is dependent
on the diverse elements in the system. The electronic sensor or
communication is one of the limbs, albeit an important one. In a
defence scenario, every element is finally tied down to a weapon
and ultimately, the total effectiveness is measured in the manner
in which this system either performs/survives or perishes. Such a
terminal evaluation, as mentioned earlier, is unfortunately
possible, only upon major encounters.
Even such evaluations are not easily tractable, given the
inevitable shroud of secrecy in the EW matters. This is more so, in

6
the ECM arena, which has assumed more glamorous and
mysterious air. Our country is no exception to this syndrome.
1.4.3 Judging Efficacy of an ECCM Element
Under the circumstances, how does one judge the efficacy
of an ECCM element? The august body of IEEE, USA, went into
the matter in the seventies. The IEEE-AES panel headed by
Stephen Johnston came up with a definition of ECCM improvement
Factor (EIF). Definition-wise, it is similar to the MTI improvement
factor in a radar receiver but is not that easily measurable, except
through results. For more complex systems connected with a
number of ECCM elements, the combined effectiveness is
measured as
(1/EIF) of a system = (1/f1
)+(1/f2
)+(1/f3
)+ ...
where, fn
’s are the EIF of individual elements. For defence related
areas, in the final reckoning, EIF calculation should take into
account all the diverse elements of a system. The terminal element
in a defence system is the weapon; its platform, deployment,
guidance and delivery. Some of these will be totally non-electronic
but still needs to be factored into the final evaluation of the
system’s survivability. With all its defects, EIF is the only defined
measure, as of this moment, to determine the efficacy of an ECCM
system.
1.5 ASSESSMENT OF THE STATE-OF-THE-ART
The development of ECCM techniques and their deployment
strategies have, by force, been driven by the Electronic
Countermeasure (ECM). The classical model of development, based
on thrust and counter-thrust, is no longer valid in the present
context, as the time needed for a new ECCM system development is
just not available during a developing conflict. This immediately
brings in the necessity of a continuous, full-time analysis of the
emerging technologies in the electronic warfare field. All over the
world, analytical work carried out in the electronic warfare is not
easily shared for the obvious reasons of compromise with the
national security. The solutions are not applicable globally either.
From a deeper examination of the subject of modern ECCM, devoted
to radar and communication area, the following pointers emerge:
(a) Sophisticated signal processing methods, especially on
multidimensional spectral estimation techniques
(b) Study and analysis of non-gaussian signal interference and the
applicable mitigation techniques

Introduction
7
(c) Artificial intelligence/knowledge-based inference mechanism for
assistance in real-time ECCM decisions
(d) Neural network-based simulation for creating a learning process
in the ECCM decision tree
(e) Prediction and ECCM efficacy evaluation techniques for validating
the simulation process
(f) Use of VLSI techniques in integrating diverse high-speed decision
logic, as well as providing specific ASIC solutions to equipment
needing secure personality modules. This also includes the
development of micro-electromechanical sensors (MEMs)
(g) Development of photonics and other multi-sensor systems for
building survivability in the networking of information
(h) Safeguards needed in the cyber world, when one builds computer-
based decision systems in the defence field.

CHAPTER 2
MODERN RADAR DESIGN ITS
DEPLOYMENT ENVIRONMENT
2.1 INTRODUCTION
Modern radar system design looks into two major phases,
the benign as well as the hostile environment. To the former, falls
the usual classification of clutter, terrain, screening, radar
horizon, mode of propagation and interference, EMC, etc. The
resultant modification to the radar performance has been studied
and well documented over the last century of radar development
in the world.
However, a radar system under Electronic Countermeasure
(ECM) and other means of hostile electronic interference operate
altogether in a different dimension. Firstly, the situation is dynamic.
The sources and the nature of interference are many. The solutions
for survival are also varied, depending on the effectiveness one seeks
to achieve. Secondly, there is no clear understanding of what was
achieved under what circumstances, and how long such a
performance can be maintained by the radar system designer. Much
of the problem in this field is due to the inevitable secrecy that
shrouds the EW world.
It then becomes essential to examine the present and
ever evolving EW technology and techniques and compare the
performance obtained with the current radar design concepts. The
limitations of some of the system concepts and in their physical
implementation are to be understood when seeking better solutions
against EW threats. Apart from all other functional and operational
requirements, the radar design needs augmentation in robustness
of operation under hostile environment.

10
2.2 RADAR PERFORMANCE
As stated, the interference to radar operation under benign
environment is understood and well documented. Analysis and
solutions are invariably available for operational conditions under
• Ground and weather clutter
• Propagation effects, angles, and anomalous conditions
• Multi-path, lobing, screening, and radar horizon effects
Most of these conditions are prominently featured when a
ground radar operates against low-flying targets. Similar situation
holds well when an airborne radar is functioning on a look-down
mode. Shipborne systems operate under various sea-states and
have solutions when they experience severe forward scatter from
the sea surface and for encountering the sea clutter. Anomalous
propagation effects are very much prevalent over the Indian
waters.
2.2.1 Two Representative Radar Models
2.2.1.1 Low flying detection model
The strength of the radar signal received by the radar
system in consideration of the earth’s influence is written in the
form
5
2/
min .=
( )
( )
4π
ϕ (2.1)
where, F (ϕ) is the pattern propagation factor. This, for small
angles of elevation
= 4 × (Height of the Transmitter) × (Height of the
Receiver)/Wavelength = 4(Ht
Hr
)/λ.
The modified radar range equation under this condition is
R
P G H H
S
H H
Const
Rt t t r t r
omax
min
= =8
4 4
8
.
(2.2)
where, Ro
is the maximum range of the radar in free space
condition. The eighth root relationship in the modified radar range
equation is to be noted.

Modern Radar Design its Deployment Environment
11
2.2.1.2 Land clutter model for radar design
Clutter reflectivity = Ω Ωo c oF RSin( ) ( )
and = ψ
= K for R ≤ Rh
= K (Rh
/R)4
for R Rh
where, R = Radar range, Rh
is the radar horizon and Fc
is the two-
way propagation factor for radar clutter path geometry.
Under the hostile environment, there is a severe restriction
imposed on the performance of any given radar, unless a suite of
ECCM features have been built into its design. For example, the
graph below (Fig. 2.1), shows how the range performance can be
almost negligible against a self-screening jammer.
BURNTHROUGH RANGE
DATA 1
DATA 2
DATA 3
S Vs RANGE
S/J Vs RANGE
J Vs RANGE
RANGE
S/J
8
7
6
5
4
3
2
1
0.6
0
0.8 1
While viewing this graph, it is to be remembered that the
jammer signal varies as R–2
and the radar signal as R–4
.
A host of relationships have been developed to describe the
radar performance under ECM1
. Modelling of the environment has
Figure 2.1. Behaviour of S/J ratio as a function of range

12
been suggested whenever analytical expressions could be derived
to represent the hostile interference. Processing decisions through
application of Game Theory have been suggested to take into
account the nature of the electronic conflict. A modified radar
range equation, in a functional form to take care of the ECCM
decisions, has also been proposed.
In general, the nature of countermoves in the radar against
ECM would be to have
(a) Reduction in the time period of signal emission
(b) Complex radar signature
(c) Highly directional beam with non-uniform scan/random
search patterns of the antenna
(d) Agility in the antenna beam as well as in the frequency of
radiation of the transmitter
(e) Sophisticated signal processing using digitally adaptive
solutions
(f) Parameter management of the radar in peace and war
situations
(g) Space and frequency diversity in the radar deployment.
These solutions are of course bought under a price, both in
terms of the cost and in the normal performance of the radar. The
system complexity increases with added pressure on the
engineering reliability. Some of the countermoves built in the
radar are short lived in terms of time element as it is relatively
difficult to configure to a new threat as fast as it is feasible with
an ECM equipment. It is indeed difficult to visualise a radar with
a new ECCM feature in the time it takes to fit a new or modified
ECM pod in an airborne mission.
Some of the complex and sophisticated processing built as
ECCM are quickly reduced in effectiveness under ECM. For
example, the linearity of processing in a coherent radar receiver is
severely impaired due to limiting or the saturation effects imposed
at the receiver front-end by a jammer. The linear chirp [of a pulse
compression design in a low probability intercept (LPI) radar] is
often degraded by the use of STC, or due to the blanking of the
portion of the expanded pulse during jamming.
Another area in which a clear understanding is yet to
emerge is in the evaluation of a given ECCM against its
counterpart ECM. Considerable interest has been shown in the
recent past1
, but there is inevitably an element of secrecy and
deliberate ambiguity on this aspect. Nor is there an accepted

13
method of assessing radar’s ECCM performance against a host of
simultaneously present ECM’s. Some of these issues have been
examined by several authors1
.
2.3 COMMAND, CONTROL, COMMUNICATION
INTELLIGENCE
When examining the efficacy and survivability under EW,
apart from the single radar detection device, the ECCM scenario
extends to the air-defence complex as a whole. In a typical modern
air-defence complex, radars of different types and functionality are
usually netted and supplemented with other types of sensors.
Such a scheme provides space and spectrum diversity and thus
renders itself less vulnerable. Consequent to this arrangement is
the inevitable necessity to collect, collate, and analyse critical data
for the final decision mechanism. The timely and proper
information flow to a command and control centre acts as a
lifeline during a conflict situation. Thus, communication networks
too become critical in judging the robustness of operation under
the EW threat.
Accordingly, a concentrated effort is called for in the
integration of the following knowledge elements: (a) expertise
developed under multisensor, real-time information flow coupled
with (b) real-time decision process.
This leads to the concept of electronic battlefield
management. The scenario is graphically illustrated below (Fig 2.2).
Figure 2.2. Electronic battlefield management
EW
THREAT
NETTED
SENSORS
NETTED
SENSORS
NETTED
SENSORS
BATTLE
MANAGEMENT
DATA
FUSION
THREAT
PROCESSING
COUNTER
ACTION

14
The concept combines a number of functions as follows:
(a) Intelligent fusion of various sensors deployed in a complex
(b) Decoding of opponent’s intention through appropriate,
knowledge-based inference machines
(c) Communication to the various echelons regarding the micro
and macro decisions
As such, there is no dispute about the speed of execution
of the above procedure (a computer-based decision will always be
faster than that of a human being who needs more time to
assimilate new and emerging facts). However, the credibility of the
automatic decision is dependent on the database and knowledge
accumulated and updated over a period. This process includes
several layers of preparation and updating cycles:
_ Documenting the ever proliferating domain of threats, their
electronic signatures, decoys, and deception methods
_ Nature and contour of one’s geographic borders and its past
history of conflict play an important role in the decision
mechanism. To cite an example, the vast ocean fronts
covering India from west to east and the economical resources
built on these, render themselves vulnerable during major
conflicts
• Sophisticated Electronic Support Measure (ESM) systems
with fast and accurate acquisition and monitoring
capabilities, programmable functions, vast memory capacity
and replay facility for simulation/training roles. The role of
ESM’s are pretty well established in the ECM arena; but
similar application should be extended in the deployment of
the ECCM response to counter the dynamic nature of the
electronic threat.
2.4 ECCM MODELLING
It is therefore, necessary to examine the issues of
survivability, with models appropriate to the present time. Few
distinct steps in the modelling process have been suggested.
2.4.1 Radar Systems
(a) Models according to functions (such as track, guidance, and
multifunction types)
(b) According to deployment (whether singly operated or in a
network environment, monostatic or bistatic mode).

15
(c) According to platforms (land-based, shipborne or airborne)
(d) According to special techniques used in the hostile/victim
systems [adaptive/electronic scanning, coded transmitters,
customised signal processing, stealth technology, anti-
radiation missiles (ARMS), decoys, etc.].
2.4.2 Communication Systems
(a) Models according to modulation types employed
(b) According to code and degree of encryption implemented
(c) Error detection and error correction schemes employed, and
(d) Deployment, networking methods.
2.5 MATHEMATICAL ANALYSIS
After describing the various models that can be conceived
for the ECCM process, it is necessary to examine the method of
analysis. The following mathematical procedures amenable to
computer oriented numerical techniques have been employed:
_ Parametric method of analysis, after identifying the
important elements of the system for ECCM operation
_ MIN-MAX theorem and application to the ECM-ECCM
matrix
_ Application of Game Theory to ECCM evaluation
_ Application of probability functions to ECCM parameters and
in their evaluations
• Invoking the figure of merit in performance of some of the
well-known ECCM subsystems.
2.6 SIMULATION
Digital computer simulation combined with hardware–in-
the-loop system, is the most effective way of combining the
analytical and the practical elements of an EW scenario. In such a
hybrid combination, the solution of a given problem can be found
on a real-time basis. However, there are a number of inexact
parameters in the process.
The immunity of the system under different jamming
threats are estimated on a statistical basis. These give an
expectation value on the performance of the system under
evaluation. The success of such an analysis depends, to a great
extent, on the capability of modelling the ECM and the victim
systems through the following steps.

16
(a) The number of independent parameters of the radar and the
probability that these parameters have been subjected to
enemy’s ESM analysis
(b) The probability that the radar parameters will be subjected to
jamming by enemy, after the necessary reconnaissance
(c) The probability with which the victim radar parameters are
jammed.
The above three steps lead to the overall probability
of the radar being jammed. The analytical determination of the
probability with which the victim system can function effectively
is fraught with considerable difficulty. However, if the radar is
assisted by its own dedicated ESM system (in the spatial, spectral,
and temporal coordinates), it becomes feasible to programme the
radar ECCM response in a more effective and analytical manner.
2.7 THE EW FLYWHEEL
The logical step leads one to have a knowledge-based, ESM
backed, ECCM response system which can be used in the
hybrid simulation consisting of digital computer coupled to
hardware-in-the-loop test bed.
The concept here is to involve an ESM system for ECCM
decision making, as much as such a system is exploited in the
deployment of the ECM function by the enemy forces. A dynamic
cause vs effect is tracked between the systems fielded by both the
forces.
The EW is a continuous game of winning over the
opponent’s use of electronics. Conventionally, the ECM users
deploy Elint surveillance to detect and map the opponents use of
their electronic gears. Typically, the ESM has all the sophisticated
system of decoding the electronic signatures of the enemy’s
transmission. The direction finding equipment supplements this
data with the angle of arrival of the intercepted signal. Such a
decoded information, rendered on a real time basis, is then used
to select the appropriate ECM for the jammer (Fig. 2.3).
It can then be convincingly argued that the Radar
Designers should use a similar decoding mechanism in order that
their ECCM response is appropriate. As further denoted in the
figure, a friendly ESM operated at the radar end would help in
decoding the ECM signal and thus help in the proper ECCM

17
selection. Such a scheme also has the beneficial feature of having
a dynamic response which is a must in all the EW encounters.
This integrated approach to radar ECCM decision making is
required both at the time of design and during deployment, where
geographical effects can also contribute to the vulnerability analysis.
REFERENCE
1. Johnston, S.L. Radar electronic counter countermeasures.
Artech House, 1979.
Figure 2.3. Selecting appropriate ECM for the jammer
ENEMY
ECM
FRIENDLY
ESM
RADAR
AND
ECCM
ENEMY
ESM
DECISION
DECODING
DECODING
DECISION

CHAPTER 3
ECCM EVALUATION–SOME MODELS
3.1 INTRODUCTION
The concept of ECCM evaluation in a radar system was
initially proposed by Johnston1
, who introduced the term ECCM
Improvement Factor (EIF). This measures the efficacy of a particular
use of ECCM (Electronic Counter Countermeasures) in a radar
system against an encountered ECM (Electronic Countermeasures).
It is a factor to be used in the evaluation, in a manner analogous to
the concept of improvement factor in an MTI processor. Although
the EIF has been introduced about three decades back, it has not
found an all-round application so far in the literatures on radar
ECCM. This is the only accepted evaluation method presently
available which is professionally recognised as a standard by the
IEEE body since 1977. Some generalised models for radar ECCM
evaluation are proposed here.
3.2 ECCM IMPROVEMENT FACTOR
By definition, EIF is the ratio of the
ECM signal required to produce a given output at the radar (with ECCM)
ECM signal required to produce the same radar output (without ECCM).
Thus, it helps in quantifying the ECCM efficacy in a system-
oriented evaluation. The Radar’s ECCM effect can be conveniently
viewed under the following generalised grouping:
• Functional (sensor-wise)
• Response to specific ECM
• Deployment type (field/environment)
• Total weapon system efficacy
In expanding the above models with appropriate examples,
the ECCM implementation and its evaluation can be examined
• As pertaining to a search, track or a weapon guidance radar, or
• According to the ECM-ECCM matrix well defined in all
literatures, or

20
• In relation to the vulnerability experienced in a deployment
pattern, or
• By determining the effectiveness and survivability as a total
weapon system against an ECM attack (such as a missile-
site radar complex with its sensors, weapons, and inter/
intra communication equipment).
The last category is what the EIF specifies as a total figure of
merit. However, the diverse subsystems and their operations (from
sensor to weapons) make it a difficult task to evaluate the result.
The nature and spread of technologies involved in such a system
makes this evaluation a complex task.
3.3 FUNCTIONAL MODELS
When broken into functional models, it becomes easier to
relate the ECM-ECCM matrix more closely to the system under
consideration.
A search radar has the primary role of searching,
identifying, and designating targets of interest. Noise (in the benign
environment) and jamming (in times of hostilities) are the two
factors it has to contend with. Figure of merit of such a radar is
easily tractable and is presently evaluated according to the
established norms of Probability of Detection Pd
and Probability of
False Alarm Pf a
. Signal-to-Noise Power Ratio S/N and Jammer-to-
Signal Power Ratio J/S are directly related to the above factors. A
number of simulation methods are available2,3
to test the radar
receiver system under different threats. Thus, a fair assessment of
the receiver system performance and its deterioration against a
given interference can be carried out.
However, when one goes from the receiver subsystem of the
radar to the other building blocks like the antenna and transmitter,
the evaluation against the jammer/s becomes somewhat
intractable. The performance of antennas on sidelobe jamming is a
function depending on a number of factors; not all of these can be
easily simulated in a laboratory. Performance of a transmitter
against jamming is again effectively assessed only through the
attendant antenna and the receiver systems.
So, in assessing the ECCM features of a radar system
devoted to a particular function, the model, to a large extent, is
simplified. However, there is still a large gap in the methods and
assessment procedures to be carried out for the system as a whole.
Hence, intermediate and somewhat localised parameters of
measurements have been resorted to in quantifying the ECCM

ECCM Evaluation–Some Models
21
evaluation; such as processing gain, cancellation ratio, J/S
measurement, burnthrough range, self-screening range, etc. These
have drawn heavy criticism in the literature2
.
Almost similar comments can be given while discussing a
tracking radar model with ECCM. This type though attracts a
different ECM-ECCM matrix. The radar function is now devoted to
tracking the target/s with a stipulated accuracy, validate the tracks
to finally guide the operation to weapon attack on the assigned
target/s. Once again, a large number of studies have been
published in the literature2
to enumerate the ECM effects and the
ECCM response of this class of radar. The quantification done is
again related to the receiver, MTI parameters and comparison
between different tracking methods against a given jamming
technique. These are however, not easily extendable to the weapon
system to which all the sensors are finally integrated. The latter
represents an altogether different class of devices, though these
may have their own components of electronics.
The Multifunction Radar (MFR) is another functional
example, though relatively complex, which is amenable to
ECCM modelling. This case effectively represents as to how the
system evaluation of EIF becomes a difficult proposition.
Sophisticated methods are required to simulate and test all
aspects of the MFR and this is an expensive and difficult
proposition.
3.4 RESPONSE TO SPECIFIC ECM
The related ECCM response of radar against an encountered
ECM is widely covered in literature4
. The success of a particular
ECCM technique against an assumed ECM threat, taken as one
pair at a time, is tangible for quick analysis. Efficacy evaluation
against multiple and simultaneous threats (such as the one from a
stand-off jammer in collusion with an on-board jammer) is a matter
of different complexity. In this context, it is relevant to point out
that the EIF is supposedly analogous to the concept and
measurement of MTI improvement factor1
in radar systems.
Nevertheless, this concept has not progressed further. To cite
examples, the measurement of improvement factor in a radar
system transcends from transmitter, STALO to the receiver.
Parameters like spectrum spread through antenna scan, clutter
modelling, clutter illumination coming through sidelobes, etc.,
support the evaluation of the MTI in a radar system. Further, a
simple relationship exists to correlate the improvement factor of

22
individual constituents to the total system (1/I = 1/I1
+ 1/I2
+ 1/I3
…..+1/In
). Evaluation like the sub-clutter visibility (SCV) relates the
improvement factor to the total system performance against clutter.
Thus, a system evaluation is made possible.
Taking this line of thinking to the area of EIF can meet with
some obstacles as a system ECCM combines a number of diverse
elements. Especially in the weapon systems, the electronics and the
armour/missile/mechanical elements co-exist and it is difficult to
determine a factor like system EIF in such cases. The most practical
thing in these circumstances is to examine the vulnerability of each
element from the EW viewpoint and take the weakest link to
represent the ultimate factor that determines the survivability of
the system.
3.5 DEPLOYMENT MODELS
The effectiveness or otherwise of ECCM in a weapon system
model depends also on its deployment pattern. One such case was
discussed in relation to the MFR model5
. Loomis has detailed an
ECCM attack pattern dependent on the system deployment6
.
Further, the efficacy of the ECCM model undergoes radical changes
depending on the platform on which the ECCM is deployed such as
ground, ship, or airborne radar2
.
3.6 WEAPON SYSTEM EFFICACY
There is no argument that the ultimate ECCM evaluation
will have to be judged through the total weapon system efficacy
against ECM. The magnitude and the diverse nature of this exercise
needs no elaboration as it includes the sensors, weapons,
communication and many decision channels. Modelling and
simulation play a big role in this regard, as it is cost-effective and
practical than the actual weapon system testing under different
conditions. The veracity of the model however, needs a large amount
of corroborative work. Experience built over a long period and final
validation with limited weapon trials are effective solutions to this
aspect. It is learnt from literature that the Patriot missile defence
system could be validated by Raytheon with very limited trials. This
was made possible by the Company as it was backed up by
enormous system simulation studies and mock-runs on a
simulator, which included ECCM evaluation.
3.7 GAME THEORY MODEL
Major conflicts in the conventional and nuclear war are
studied through Game Theory models. Weapon systems and their

23
effectiveness have been traditionally studied through such
well-established methods.
3.7.1 Case Study 1
A game theory model, as a strategy applied to radar
detection under ECM attack, was analysed by Nilson7
in 1959. He
described various functions of a radar model and the related
strategies against a jammer. The model chosen employed a matched
filter in the radar receiver, which he proves to be an optimum game
theoretic filter.
Concentrating on the anti-jamming strategy as applied to
the transmitter, Nilson emphasises on the optimal use of the power
spectral distribution for the radar waveform design. The various
pay-off functions chosen related to the role of radar in detection,
tracking, and velocity estimation. It is pertinent to point out that
such results obtained through game theory in 1959 find
corroboration in the work by Gager8
. Though Gager had based his
arguments altogether on different and practical consideration, yet
he still arrived at the same conclusion.
3.7.2 Case Study 2
One more example can be cited from applied game theory to
illustrate its application to ECCM modelling against deception.
Repeater jammer, decoy, and chaff play their share of the game in
electronic warfare. Surprise and deception are their end goals. Thus
their roles appear to be not very different from those observed in
conventional warfare.
Axelrod9
has attempted to model policy-oriented theory of
deception and counter-deception in war games. This modelling is to
serve four important end uses:
(a) To make a realistic assessment between two extreme
viewpoints or results
(b) To evaluate the input information which is often incomplete
and at the control of the opposition
(c) To act as a logical and conceptual guide to future action, and
(d) To evaluate the total performance in a given setting.
Borrowing on the model discussed by Axelrod, one could
extend the argument of employing minmax game theory approach
to electronic deception. The model stipulates how to maximise the
pay-off when pure or mixed strategies are encountered. The

24
C
A
B
D
No Reaction
Reaction
Real
Target
Decoy/
Deception
Value
to
Attacker
M
Attack
C
A
B
D
No Reaction
Reaction
RealFake
Value
to
Attacker
M
Attack
Figure 3.2. Weapon system
Figure 3.1. Defence
pay-off involved in this case is one of opposition’s penetration of
other's defence and/or other's survivability against it. Based on the
arguments given, the results are shown below (Fig. 3.1 and 3.2).
Figure 3.1 shows the response between an attacker and a
defender, both initially following pure strategies (of attacking/faking
vs reacting/not reacting). The pay-off is indicated in terms of a value
to the attacker. Assuming this as a zero-sum game, the value for the
defender will be negative of this quantity. It can be seen that the
attacker gets the best value at B and worst pay-off at D.
Using minmax criterion of mixed strategies by both the
parties (involving a judicious probability mix between the real and
the fake actions), the minimum pay-off that can be obtained is
shown by a dotted curve. ‘M’ indicates the maximum of the

25
C
A
B
D
No Reaction
Reaction
Reaction with Warning Device
RealDecoy
Pay-off
to
Attacker
minimum pay-off that will be the outcome of this strategy for the
attacker.
Figure 3.2 similarly indicates the situation when the
previous example is translated to show the effect of a decoy or a
deception jammer against a weapon system. The weapon is
assumed to be guided by its electronic sensors. The reasoning is
similar to that of Fig. 3.1 provided by Axelrod9
.
The simple model of Fig. 3.1 can be further refined when a
warning system is added to the environment. Such a system
enhances the capability of survival. Of course, the information
available to the warning device may be incomplete or partially
correct in a situation of conflict, but its very presence is considered
significant to the decision making. Depending on the discriminatory
value attached to the warning device, the pay-off to the defender is
improved as shown below (Fig 3.3).
The basis used by Axelrod for his model coincides with the
usual radar concepts of detection and false alarm probability, with
normal distribution. In this context, the case of the ESM receiver
is realised as a warning system to aid the ECCM response.
Borrowing on the above model, the response of a weapon system
with ESM warning can be viewed with similar results in Fig. 3.3.
Concept like Constant False Alarm Receiver (CFAR) can also be
utilised to describe the strategy for ensuring an assured pay-off
under deception. It is necessary to point out that the concepts of
game theory applied both by Nilson7
and Axelrod9
have been
accepted by radar engineers and as such these concepts form
attractive modelling possibilities.
Figure 3.3. Pay-off in the presence of a warning device

26
REFERENCES
Artech House, 1979, Chapter 9.2, pp. 499-501.
Artech House, USA, 1979.
3. Military electronics/countermeasures, 1980, 3 12.
IEEE Trans. Aerospace Elect. Syst., 1978, 14(1), 109-17.
5. Subramanian, A.K. ECCM improvement factor considerations
in a multi-function radar. In Proceedings of the International
Radar Symposium, IRSI-83, India, 1983. pp. 587-92.
6. Loomis, R. Threats and techniques. Electronic Progress, 1975,
17(3), 17-25.
7. Nilson, N.J. An application of the theory of games to radar
reception problems. In IRE Convention Record, Pt.4, 1959.
pp. 130-40.
8. Gager, C.H. The impact of waveform bandwidth upon
tactical radar design. In Proceedings of Radar-82, UK.
pp. 278-82.
9. Axelrod, R. Coping with deception: Applied game theory. In
Proceedings of the Conference at the Institute for Advanced
Studies, Vienna, 1978. pp. 390-405.

CHAPTER 4
MODELLING FOR ELECTRONIC CONFLICT
THE BURNTHROUGH EQUATION MODEL
4.1 BACKGROUND
The burnthrough equation is a significant parameter in the
discussion of the Radar-ECM scenario. The radar detection
depends on the R–4
relationship whereas the jammer coverage
range is determined by the R–2
dependence. The difference is due
to the physical fact that the radar has a two-way transmission
path for its detection capability; it is easily perceived at the same
time that the jammer needs only to radiate its signal and reach its
victim on a one-way transmission path. If one considers a target
carrying its own on-board Self-Protection Jammer (SPJ), the
following equations would indicate the ranges where the jammer is
dominant over the radar and the juncture when it becomes
vulnerable to its skin detection by radar in spite of its EW suite.
The signal power S received by a radar receiver is given by







 φθφθσφθ








π LLR
AGP1
=S
rtt
,r,,tt t
4
111111
2
)(
)()()(
)4(
(4.1)
and the interfering power from an active jammer ‘J’ by
2
2222 1)()(
4
1











 φθ



 φθ




π
=
jjj
,jj
r
r,r
RLB
GP
L
BA
J (4.2)
where,
Radar Parameters
Pt
= Peak power of radar transmitter
Gt
(θ1
,φ1
) = Transmitting antenna gain in the direction of the

28
target (function of its azimuthal and elevation
angles)
Ar
(θ1
, φ1
) = Effective aperture of the receiving antenna
presented in the direction of the target
Ar
(θ2
, φ2
) = Effective receiver antenna aperture presented in
the direction of the jammer [If the target and the
jammer are same – as in self-protection
jammers (SPJ’s), then θ1
= θ2
and φ1
= φ2
]
Br
= Radar receiver bandwidth
Lt
= Transmitter losses, and
Lr
= Receiver losses
Jammer Parameters
Pj
= Jammer power
Gj
(θ2
, φ2
) = Jammer antenna gain in the direction of the
radar
Rj
= Jammer range to the radar
Bj
= Jammer bandwidth, and
Lj
= Jammer losses
Target Parameters
σt
(θ1
, φ1
) = Target cross-section presented in the direction
of the radar
Rt
= Target range to the radar.
Hence, the ratio of the jammer to the target signal power is










φθφθ
φθφθ




φθσ
π
LR,AB,GP
LR,AB,GP
,
4=
S
J
jjrjtt
ttrrjj
t
)()()(
)()()(
)( 2
1111
4
2222
11 (4.3)
and the significant point to note here is that the ratio is
proportional to [Rt
4
/Rj
2
].
In the case of a target carrying a jammer aboard, it is clear
that Rt
= Rj
, the angular directions θ1
= θ2
= θ and φ1
= φ2
= φ, thus
making the antenna receive aperture Ar
(θ1
, φ1
) to be equal to
Ar
(θ2
, φ2
). Resetting the Eqn. 4.3 for this case, the J/S ratio is
simplified as Eqn. 4.4.

Modelling for Electronic Conflict:The Burnthrough Equation Model
29
J
S
P G B R L
P G B Lt
j j r t
t t j j
=


















4
2
π
σ θ φ
θ φ
θ φ( , )
( , ) ( )
( , ) (4.4)
4.2.1 The Burnthrough Range
The Burnthrough range is denoted by Rss
. Signal from the
skin echo of the target varies as (range)-4
and the interfering
jammer signal as (range)-2
. Hence, the radar has to compete
against the jammer interference, especially at the long range, in
finding the target. However, as the target flies towards the radar,
the target strength increases to 12 dB when the range is halved.
The jammer power, in contrast, gains only 6 dB for a similar
situation. It is clear then, that there will be a crossover range
R = Rss
, where the J/S ratio becomes unity. Below this range, the
skin reflection from the target becomes a dominant factor for the
detection criterion of the radar. Above Rss
, the jammer dominates.
Thus, the value of Rss
of the radar (denoted as its burnthrough
range) is a parameter which both the parties of the electronic
conflict wish to capitalise upon. The ratio Rss
/Rf
which is
Radar’s maximum range under jamming environment
Radar’s maximum range for the same target under
benign environment
can also be used to characterise the performance of a radar under
the hostile interference. The jammer would try to reduce this
factor while the radar designer would like to maintain this ratio as
near to unity as possible, employing suitable ECCM. Rss
can then
provide a measure of performance index for the chosen ECCM
operation.
The general relationship from Eqn. 4.3 can be rearranged
to quantify the interdependence of the radar range with the
various parameters of the radar-jammer scenario:
















φθ
φθ












φθ
φθ












π
σ
)/(
)(
)(
)(
)(
)(
2
22
11
22
11
4
JSL
LR
,A
,A
B
B
,G
,G
P
P
4
=R
t
jj
r
r
r
j
j
t
j
tt
t (4.5)
4.2.2 Escort Jammer
For a stand-off or escort jammer, Rt
≠ Rj
and if the jammer
is not falling on the same line connecting the radar and the target,

30
the receiver antenna apertures for the signals are not equal, i.e.,
Ar
(θ1
, φ1
) ≠ Ar
(θ2
, φ2
). The above equation remains
unaltered in this case.
For the on-axis stand-off or escort jammer, the following
holds good:
Rt
≠ Rj
but Ar
(θ1
, φ1
) = Ar
(θ2
, φ2
). Equation 4.5 simplifies to
( )
( )
( )
























φθ
φθ














π
σ
)(
2
22
114
S/JL
LR
B
B
G
G
P
P
4
=R
t
jj
r
j
,j
,t
j
tt
t (4.6)
For both the conditions, the Eqns. 4.5 and 4.6 can be used
to estimate the maximum range of detection (by skin reflection) of
the target by the radar. This provides the performance index
known as the mutual screening range.
4.2.3 On-board Jammer
For a on-board jammer carried by the target, the scenario
reduces the general Eqn. 4.4 to the case of the burnthrough
range. This is also known as the self screening range for the
jammer.
4.2.4 Repeater Jammer
With regard to repeater jamming, the conflict becomes
different. The jammer here re-radiates the received energy (with its
modification and gain) along the same or different direction. The
J/S ratio is then given by suitable substitution as
(i) Condition: Rt
= Rj
= R, Bj
= Br
and Ar
(θ1
,φ1
) = Ar
(θ2
, φ2
) = A.












φθ
φθ










π
φθσ
)()(
)()(
22
11112
S/JL
L
G
G
P
P
4
=R
t
j
,j
,t
j
t,t
(4.7)
(ii) Condition: Rt
= Rj
= R and Bj
= Br
but Ar
(θ1
,φ1
) ≠ Ar
(θ2
,φ2
).
(Jammer’s repeater action is seen through the sidelobes of
the radar beam)










φθ
φθ








φ
φ










π
φθσ
)()(
)(
)(è
)(è)(
22
11
22
11112
S/JL
L
A
A
G
G
P
P
4
=R
t
j
,
,
,j
,t
j
t,t
r
r
(4.8)
(iii) Condition: The jammer collects the radar power through its
antenna and re-radiates with its own gain and sends it back

31
along the same direction. Hence, Rt
= Rj
= R, Ar
(θ1
, φ1
) =
Ar
(θ2
, φ2
) = A and Bj
= Br
.
If Gj1
= Repeater’s receive antenna gain, Gx
= gain
(unsaturated) of the jammer, and Gj2
= gain of the repeater’s
transmit antenna, then the total system gain G at the jammer is
given by G = Aj 1
Gx
Gj 2
= [λ2
/(4π)][Gj 1
Gx
Gj 2
]. Hence, the power
returned by the repeater jammer to the radar is
J
P G
R L
G G G
L R
A
L
t t
t
j x j
j r
=




































( , ) ( ) ( ) ( ) ( )
( )
θ φ
π
λ
π π
1 1
2
1
2
2
2
4 4
1
4
(4.9)
and the signal due to the target’s echo is
S
P G A
R L L
t t t
t r
=
















1
4
2
1 1 1 1
4
( )
( , ) ( , )
( )π
θ φ σ θ φ
and thus, the ratio J/S is given by






σ
=





σ










π
λ
tjtj
jxj
L
G
L4
GGG
=
S
J )(jammerofgainSystem1
)(
))()()( 2
2
(1
(4.10)
It is seen from the above equation that with suitable
overall gain G, the jammer can easily dominate the radar’s
performance. If the jammer is employed on-board a stealth
system, there is a further advantage due to the reduction of the
target’s echo σt
, and consequently, a similar reduction in the
burnthrough range Rss
.
4.3 COMMENTS ON THE BURNTHROUGH RANGE
EQUATION
Johnston1
has given the most severe criticism on the
concept and the utility of the burnthrough range. He lists several
factors against the dependence on this parameter and it is
necessary to summarise the major problems as he views them:
(a) Most of the treatments on the Rss
factor do not include all the
essential variables of the ECCM-ECM matrix, or the same
variables from case to case; further, these parameters are not
defined to its entire capability in their respective usage

32
(b) It does not include the effect of ECCM
(c) Effect of various antenna coverages is not reflected in such a
simple representation of Rss
(d) Fluctuation in the target cross-section during its flight is not
accounted for
(e) Modern methods of signal formulation, signal detection
criteria, flexible antenna scans, etc., are not properly reflected
in this simple relationship
(f) There may be more than one unique range, definable for the
burnthrough concept
(g) Finally, the performance index associated with burnthrough
range applies only to cases of denial ECM’s. It does not cover
aspects of deception, confusion jammers and threats like anti
radiation missile (ARM).
Further analysis on these aspects is carried out in the
ensuing paragraphs.
4.4 A RELOOK AT THE BURNTHROUGH RANGE
RELATIONSHIP
A more useful form of the Eqn. 4.5 is examined in this
section to try and provide answers to the comments recorded
above.
First of all, the equation is rewritten in terms of energy
terms as
( )
( , ) ( , )
( , )
( , )
( , ) /
R
E G
L
L
E G
A
A
R
S Jt
t t t
t
j
j j
r
r
j4 1 1 1 1
2 2
1 1
2 2
2
4
=










































σ θ φ
π
θ φ
θ φ
θ φ
θ φ
(4.11)
It is preferable to substitute energy term instead of power
in the equation. This will enable the definition of different types of
radar waveforms, with diverse spectral density distributions.
Hence, it is most suitable to address the situations under radar
ECCM.
Secondly, the energy term Et
= Pav
to
(where, Pav
is the
average power of the radar and to
– the duration of antenna dwell
on the target), is a more meaningful term than Pt
. For the
rectangular shaped radar pulse, Et
= (Pt
) [Pulse length (τ)]. The
jammer output energy is readily represented as Ej
, jammer power

33
per unit bandwidth (W/Hz). The S/N power ratio associated with
the radar detection can be similarly modified to Es
/No
, where, Es
is the signal energy and No
is the noise energy (i.e., noise power per
unit bandwidth).
These changes have already been introduced in the
literature2
but have not been uniformly applied as standard
parameters in the radar range equations.
One important point to analyse in the burnthrough
equation is to find ways and means to keep it flexible and
comprehensive enough to cater for the requirements of the radar
ECCM community. Thus, efforts must be made to treat the
parameters of the range equation as functions of a number of
variables, which are valuable from the ECCM front. This will
ideally suit the dynamic behaviour of the ECM vs ECCM conflict.
The resultant effect on the system performance can then be
visualised through representative modelling and computation, all
of which can now be carried out by a modern desktop computer.
4.4.1 Dynamic Radar Range Equation
A dynamic radar range equation of the following form,
operating in a denial type of ECM environment is proposed as
)]([)]([
(Jammer)][)]()]([)]([
)(
65
43214
DFLF
FFGFEF
=R4 t
t
σ
π (4.12)
F1
(E) – a function of radar transmitter characteristics [energy,
waveform, modulation, wavelength, PRF
characteristics, types of transmission (continuous
wave, interrupted continuous wave, pulse, burst
mode), tunability/instantaneous bandwidth of the
source, etc. ]
F2
(G) – a function of radar antenna behaviour (R, θ, φ),
(aperture/λ2
), beamwidth, coverage patterns, variable
beam coverage and scan rate, sidelobe levels, time of
dwell, flexibility available on the antenna operational
characteristics, etc.]
F3
(σt
) – a function of (λ, θ, φ) radar cross-sectional parameters of
the target as a function of wavelength and aspect
angles
F4
(Jammer) describes all the functional variables and capabilities
associated with the jammer [frequency range,
bandwidth and energy capabilities, sweep rates,
modulation schemes, and the known/assumed

34
capabilities of its ESM suite]
F5
(L) – is the function associated with the losses in the radar
as well as the jammer, with particular reference to
their variations under different modes of operation in
a ECM vs. ECCM encounter [Loss in the transmission-
reception chain, antenna losses, scan losses,
processing losses in the signal/data processing
chains, etc.], and
F6
(D) – includes all the functions for various detection criteria
employed in the radar from time to time, suiting the
ECCM response.
The utility of such a form of equation for the burnthrough
relationship is examined next, with the help of suitable radar
models. The applicability of computer analysis to handle a variety
of such functions and parameters becomes self-evident.
4.5 SEARCH RADAR MODELLING FOR ECCM
Utilising the new form of Eqn. 4.12 for typical search
radar, the following functions for the radar variables can be
defined for the ECCM role.
4.5.1 Functions of Radar Variables
F1
(E) represents the energy function for the transmitter.
This is dependent on a number of variables which are
representative of the ECCM capabilities in this part of the radar
system. In general, it can have a number of sub-sets, single or in
combination of the following parameters:
F1
(E) – function of the radiated energy from the radar [This
could be of the form: continuous/switchable frequency agility
(used as an ECCM for the de-correlation of clutter and reduction
of target glint), control of average power Pav
, pulse length τ, time
on target to
, multiple PRF, and coded pulses for LPI, etc.,].
(a) In the most simplest form, Et
= Pav
to
. Attempting a variational
parametric analysis3
,
[ ]∆E P t
P
P
t
tt av o
av
av
o
o
(
( ) ( )
change in energy) =
δ δ
+








If the transmitter tube has variable average power rating or
if the antenna dwell time varies, there is a change in the radiated
energy on the target. If both could be varied as independent
variables simultaneously, the energy management has two

35
degrees of freedom (DOF's) on the target to cater for a given
detection criterion. These options give an important ECCM feature
for improving the burnthrough range.
(b) If the search radar employs a mechanically scanned
antenna, δ (to
) = 0 as the time on target cannot be varied.
Then the transmitter parameters are the only ones available
for the energy management:
δ (Pav ) = δ [(Pt
- peak power) (τ - pulse length) (fr
- PRF)].
= + +








Pav
t
t
r
r
P
P
f
f
δ δ τ
τ
δ( ) ( ) ( )
Usually the variation available in Pt
is restricted. τ is also
restricted in simpler radar designs, to cater for a given range
resolution; but in LPI radars using pulse compression, there is
scope of increasing the pulse length (and hence Pav
) and
simultaneously achieving the range resolution on the receive
mode. Variable PRF is yet another ECCM parameter for increasing
the average energy, even a mandatory function in airborne
systems to achieve proper detection of target against clutter.
(c) In radars employing phased arrays,
∆Et
= δ (Pav
) + δ (to
), as both variations are independently
possible. The additional DOF, δ to
, can be further expanded to
include some more variables which are useful for the ECCM
function:
δ δ t( )to
b
s
s=






Ω
Ω
where, Ωb
is the solid angle subtended by the antenna beam, Ωs
is
the solid angle of the volume search of the radar, and ts
– scan
time/frame time of the search radar. Thus the variations due to
beamwidth (possibly as a function of elevation angle), the angle of
scan, and frame time for search can all be simulated to assess the
end result against a given scenario. Phased arrays are expensive
to implement, and hence, a cost function can also be added to
these variables to obtain a cost-effective combination of the
parameters and their extent of variation. Such a step is definitely
indicated in the case of a multifunction phased array system4
.

36
4.5.2 Antenna Function
The antenna function F2
(G ) can be equated to
G (θ, φ) × g (θ, φ), where, g is the ratio of the main-lobe to the
sidelobe, as a function of θ and φ. In this form, the gain of the
radar antenna can be described as a variable function wrt the
aspect angle of the antenna-target geometry, and as such can be
used to denote a variety of functions:
[ ]
δ
δφ
θ φ θ constant
G( , ) = and [ ]
δ
δθ
θ φ φ constant
G( , ) =
are variables describing the gain change of the radar antenna in
the two principal planes. Normally, in the case of a mechanically
scanned antenna, [ ]
δ
δφ
θ φ θ cons
G t
( , ) tan= = 0, as the azimuthal
beamwidth is held constant at each elevation bracket. But
[ ]
δ
δθ
θ φ φ constant
G ( , ) = could be used to describe aerial function
with various elevation coverages. For example, the function
G (θ, φ), where
G (θ, φ ) = G0
, θ0
≤ θ ≤ θ1
and
G (θ, φ) = G0
Cosec2
(θ), θ1
≤ θ ≤ θ2
would represent a
cosecant-squared shaped beam coverage in the elevation plane for
all azimuthal angles.
Or in discrete form, the expression,
G (θ, φ) = G1
(θ, φ) + G2
(θ, φ ) + G3
(θ, φ) + G4
(θ, φ) (4.13)
[where each gain function Gx
(θ, φ ) exists only for a specified
elevation bracket], would be handy for describing a series of
stacked pencil beams in elevation.
In phased array apertures, control is available in both the
planes and the antenna elements are each addressable and
controllable.
Another related antenna function is the sidelobe
control ‘g (θ, φ)’. This is necessarily to be viewed along with the
main antenna gain function ‘G (θ, φ)’, as the change in one
parameter affects the other5,6
. Hence, the variation of the product
[G (θ, φ ) g (θ, φ )], when optimised for antenna gain is

37
{ }
d
dG
Gg
g
dG
G
g
dG
G g g= + = − =
δ δ
0 . This form of the
expression takes into account the opposing nature of the main
beam and the sidelobe gain characteristics.
4.5.3 Jammer Function
Although these variables are not under the control of the
radar, the very presence of the jammer signal through the radar
receiver, is an indication of counter action. A knowledge of the
nature of emission from the jammer [Sj
( f ) − the spectral density
function] can generate some optimum ECCM response at the
radar site7
. Before the jammer operation, an important function of
the opposing force is to obtain information on the radar signature
through its electronic intelligence (ELINT) system. In this respect,
a performance criterion has been mentioned8
for the radar (in the
form of delay of such information to the enemy ELINT system), by
the term robustness. This is defined as the ratio of the range at
which the ELINT receiver can detect the radar signal Re
, to the
maximum range of the radar Rmax
for the target carrying an
on-board ELINT system:
( ) eerr
rrree
r
r
e
N/SBGG
N/SBGG
R
R
R
)(
)(
4π= (4.14)
where, the subscripts ‘r’ and ‘e’ stand for the radar and Elint
systems, respectively. It can also be observed that all the radar
parameters are from the equation governing Rss
(Eqn. 4.4). In fact,
Johnston has suggested that the range Rr
should actually
correspond to the burnthrough range. It is then noticed that the
robustness factor is reduced by the jammer activity:
2
)(
)()(
)(
)(
)4(
jtsr
rjjr
eerr
rrree
r
r
e
RTKN/S
AERPJ/S
N/SBGG
N/SBGG
R
R
R
σ
π= (4.15)
F3
(σ ) and F5
(L) are factors which are difficult to prescribe
accurately. However, their estimates (mean/rms/average values),
whenever available, can be used to improve the accuracy of the
range calculations.
F6
(D )–the S/N energy ratio criterion for detection varies
with different functions of the radar. Associated with this is the
type of signal processing performed and the related loss/gain

38
margins. It is also possible to add the effects of sensitivity time
control (STC), by a range-dependent weighing to this function.
4.6 LOW FLYING TARGET DETECTION MODEL
The search radar function is considerably affected when
viewed against low-flying targets with their own ECM’s. This is due
to the multi-path effect of the antenna beam at low elevations as
well as that due to surrounding clutter. Taking the multi-path
effect as most dominant, it has been shown9
that the ratio
2
1
][]
4
[ spacefreeinRange
HH
spacefreeinRange
altitudelowatRange at
λ
π
=
where, Ht and Ha represent the height of the target and antenna,
respectively. Although the relationship is an approximation, it
serves to show the decrease in the range performance, which can
be duly accounted for, while formulating the burnthrough range
under the low-flying condition of the jammer platform.
REFERENCES
Artech House, 1979. pp. 493-97.
2. Skolnik, M.I. Radar handbook. pp. 1-6.
3. Gutsche, S.L. et al. Radar ECCM. Artech Book House, 1979.
pp. 531-46.
4. Subramanian, A.K. ECCM improvement factor consider-
ations in a multifunction radar. Proceedings of international
radar symposium. IRSI-83, India, 1983. pp. 587-92.
5. Rudge, A.W. et al. Radar ECCM. Artech Book House, 1979.
pp. 195-204.
6. Hsiao, J.K. Phased array sidelobe level gain, beamwidth, and
error tolerance. Proceedings of radar conference, Paris, 1984.
pp. 304-08.
7. Nilsson, N.J. An application of the theory of games to radar
reception problems. IRE convention record, Part 4, 1959.
pp. 130-40.
8. Shenoy, R.P. Evolution of radar–An Indian point of view.
Proceedings of radar conference. Paris, 1984. pp. 5-9.
9. Maksimov, M.V. Radar anti-jamming techniques. Artech
Book House, 1979. pp. 17-18.

CHAPTER 5
LOW PROBABILITY OF INTERCEPT
SEARCH RADAR MODEL
A search radar system has the primary function of providing
the best possible detection at the best range, over an expected
volume of coverage. A large amount of electromagnetic (EM) energy
is required to accomplish this task. This factor becomes its
vulnerability as hostile receivers can sense the radiation, study its
characteristics and use the information for jamming and other
types of electronic countermeasures. From the point of view of the
ELINT (Electronic Intelligence) system, it is to be noted that the
fundamental physical law governing one-way reception is a factor
quite favourable to it.
The design features that optimise the radar's role, both for
its intended detection function as well as for providing protection
from the interception by hostile systems, are classified under the
Low Probability of Intercept (LPI) design.
An LPI radar, by its inherent design requirement, either tries
to reduce the time available for interception or makes the
recognition of its signature a low-probability event. The LPI design
may include the following features:
• Agile and flexible antenna scan programmes
• Low antenna sidelobes
• Variable transmitter parameters
• Frequency agility
• Intra-pulse coding and coherent signal processing
• Bistatic operation.
5.1 RADAR DETECTION LPI
Requirement for radar detection and LPI consideration is
not always synonymous. Hence, the designer is required to evaluate
the influence of the radar parameters in meeting the dual
requirements and arrive at an optimum, if not the best, solution.

40
The guiding principle is to ensure that the radar's intended role is
not seriously compromised during hostile electromagnetic
interference.
5.1.1 Detection
The performance of a surveillance radar is specified in terms
of positively detecting a target or a group of targets in a given time-
frame by searching a given volume of space. For discussion on LPI
aspects and volumetric coverage, the radar range equation is
modified1
as
Power-aperture product of the radar =
PA
n SNR
N
=
R
T
( ) ( )4
4
π
σ
Ω
Γ
(5.1)
where
P = Peak power of the radar transmitter
A = Effective antenna aperture of the transmit beam
R = Range of radar
Ω = Solid angle of the radar's volumetric coverage
n = Noise power of radar receiver/Hz
SNR = Receiver Signal-Noise Power ratio required for a given
detection criteria
σ = Target cross-section
T = Time taken for a single scan of the antenna
Γ = Duty ratio
N = Number of receivers assuming that the radar
transmits in a fan beam coverage; while on receive
mode, it has multiple, independent receive beams in
the elevation to define the elevation plane better
N = 1, if transmit and receive beams are the same.
5.1.2 Search Antenna
The effective transmit antenna gain is
G = (4π Α)/λ2
= (4π)/(τ Ω/T ) (5.2)
where
λ = Wavelength of transmission
τ = Beam dwell time
Ω = Solid angle of search volume of the radar
T = Scan time
Low sidelobes are part of the search radar antenna design to
cater for the detection of low-flying targets against clutter; further,

Low Probability of Intercept Search Radar Model
41
this also helps in reducing the probability of jamming through the
sidelobes. The low sidelobe design thus contributes effectively to
both the aspects of performance and survival. These designs,
however, are accompanied by decreased antenna radiating
efficiency. To compensate for this, one has to go for longer scan
times to improve the signal strength, while keeping the same
physical aperture of the antenna. There is not much of a choice in
the wavelength of operation (typically it is around L and S bands for
long range search) as large microwave power is to be generated from
the transmitter.
5.2 INTERCEPT RECEIVER
It will be equally necessary to examine the electronic warfare
concept from the interceptor platform. It wishes to capture the
radar signal for finding its coordinates as well as derive intelligence
on the nature of its signal. The sensitivity of its receiver can be
expressed2
as
Smin
= ni
SNRi
(Gi
)(B1i
)γγγγγ
(2B2i
)1 – γγγγγ
(5.3)
where
ni
= Interceptor receiver noise power/Hz,
SNRi
= Threshold signal-to-noise ratio at the interceptor
receiver
Gi
= Receive antenna gain
B1i
= Pre-detection receiver bandwidth
B2i
= Post-detection receiver bandwidth
γ = A factor varying between 0 (when two bandwidths are
comparable) and 0.5 (when B1i
B2i
).
To acquire the intended radar signal from a long range, the
interceptor has only a few choices in improving its receiver
sensitivity, increasing Gi
, and reducing B1i
and B2i
. All of these do
have practical constraints. The gain of the antenna has to be
reckoned by the demand for wide frequency range coverage. The
wide-open receiver front-end bandwidth B1i
is necessarily kept
higher to improve the probability of intercept (PoI). Hence, a finer
beam of the receiver antenna, coupled with reduced pre-detection
bandwidth will mean a fall in the PoI for the interceptor. The
reduction of B2i
will lead to lower measurement bandwidth (target
characteristics and resolution). There is scope for compromise
here, without seriously impairing the main goal of achieving the
desired PoI at the best possible range.

42
5.3 INTERFACE BETWEEN RADAR INTERCEPTOR
With the relation equations concerning the radar and the
interceptor, it is now possible to analyse the interaction between
these. The influence by the jammer on the radar could be viewed
through a connecting equation:
J = Sj
N Ar i
Br
(5.4)
where
J = Jammer power coupled to the radar
Sj
= Jammer radiated power/Hz (spectral radiance)
N = Number of independent receivers on radar
Ar i
= Effective receive aperture of the radar antenna
presented in the jammer direction
Br
= Bandwidth of radar receiver.
5.3.1 Effect of Receiver Aperture
Even a cursory look at the above equation reveals that the
best reduction of the coupled jammer power at the radar receiver
could be achieved by presenting the least antenna aperture towards
its direction. Since, the geometry between the jammer (usually
airborne) and the radar is variable in space as well as in time
domain, the solution is to cater for a sharper main beam, with low
sidelobes for the radar antenna design. This also aids in the radar
detection sensitivity but comes with penalty on the size of the
antenna; low sidelobe synthesis essentially means a highly tapered
antenna illumination, resulting in low aperture efficiency. This can
pose a major problem for a long range search radar when it
functions as a mobile system. With multiple receivers, this is likely
to be more demanding than implementing low sidelobe design on
the transmit aperture.
The limit set on the search antenna aperture vis-à-vis its
usual wavelength of operation (around L S bands) has already
been commented.
5.3.2 Conflicts
In terms of conflict between detection and LPI functions for
the radar, it is seen that though the multichannel receivers (N) are
helpful for detection, these do couple jammer power to the same
degree as the number of channels provided. It is also observed that
the radar transmit antenna should have a better gain than that of
the receive mode, to maintain LPI characteristics, though in terms
of detection criterion, the reverse holds well.

43
5.3.3 LPI Modulation Scheme
Distinct modulation schemes, like digitally coded pulse
modulation, are employed in modern radar designs. This is helpful
in detection and implementation of LPI characteristics. The long-
coded pulses with pulse compression schemes, help in reducing the
transmitter peak power requirements. Depending on the
complexities involved in the pulse coding, the transmitter signature
is sought to be guarded against classification by an eavesdropping
receiver during its listening period.
5.3.4 Interceptor Receiver Bandwidth
This receiver bandwidth, as seen from Eqn. 5.3, can vary
from
Bi
= Order of 2B1i
or 2B2i
(when the two bandwidths are
comparable)
= (2B1i
B2i
)0.5
when B1i
B2i
To increase its acquisition range, the interceptor has to
improve the receiver sensitivity (Eqn. 5.3). If the post-detection
bandwidth is reduced to achieve this, the interceptor loses its ability
to identify and classify the emitter but still retains its ability for
longer-range acquisition. This could be one of the practical
compromises, which the ECCM community has to be aware of and
consider in the radar design.
5.4 LPI–ECCM
The LPI radar, by its inherent design requirement, tries to
reduce the time available for interception and/or make the
recognition of its signature a low-probability event. In this sphere,
the elements of design are traceable to the same basic philosophy
that governs the ECCM capability of the candidate radar system.
The essential difference though, is in the stage of implementation
during operation. The process of interception is a silent function
that precedes the eventual ECM thrust on the radar. The LPI
concept is to attract less attention (interception) from a hostile
electronic snooper, and thus, its function can be considered as a
defensive measure. The role of ECCM is to offer a counter (offensive)
response in the presence of a threat. Both measures aid in the
survival of the radar system under the EW environment.
In this context, Johnston3
has defined a new set of radar
design measures under the name counter ESM (CESM). Referring
to Fig. 5.1, it can be seen that the solution caters to the dual needs
of a LPI radar system.

44
5.5 LPI–ECCM RADAR MODELS
5.5.1 Radar LI Interceptor
From Wiley4
, the ratio of the ELINT range Re
to radar range
Rr
is given by
( )( )R
R
G G
G G
L
L
e
r
r
te e
t r
e
r
R=






















4 1
1
2
π
δ σ (5.5)
The subscript ‘e’ and ‘r’ stand for ELINT and radar,
respectively and other symbologies are according to the standard
radar range equation. The factor ‘δ’ is the ratio of ELINT receiver
input power required for detection to the power needed at the radar
input for detection. The aim of the LPI radar is to reduce the value
of the ratio given in the Eqn. 5.5, which makes Re
≤ Rr
.
If the interceptor was to be on the sidelobe of the victim
radar, then
2
1




π
δ
4
G=Rr metres (5.6)
for Gte
= Ge
= 1, σ = 1 m2
, Le
= Lr
, Gt
= Gr
= G, and for the limiting case
of Re
= Rr
.
If the interceptor comes on the main beam of the victim
radar, then under the same conditions,
G=Rr
2
1
4 



π
δ metres (5.7)
Given the practical constraints of achieving high gain for
radar antennas (along with the sidelobe reduction), greater
LOW PROBABILITY
OF
INTERCEPT
(LPIn)
LOW PROBABILITY
OF
IDENTIFICATION
(LPId)
CESM
Figure 5.1. Counter ESM

45
attention is to be paid in terms of increasing ‘δ’, so that parity in
detection is obtained by radar against detection range of the ELINT.
This is done through the control of transmitter waveform (coding,
agility, etc.) and attendant signal processing, as shown in the next
section.
The processing gain ratio is again provided by Wiley4
as
2
1
0
2
1
][
Elint
Radar BT
B
B=
PG
PG
rfe
r









 (5.8)
Letting B = Brf
, the above ratio becomes equal to [BT0
]0.5
, the
square root of the time bandwidth product of the radar system,
with T0
indicating the coherent processing time. Hence The ratio ‘δ’
now simplifies to
[ ]2
1
0
)(
)(
BT
BN
BN
PG
PG
S/N
S/N
=
r
e
e
r
r
e α













δ (5.9)
Thus Rr
from Eqn. 5.6 is proportional to [BT0
]1/4
for providing
the quiet range in a LPI radar system. This can give a clear picture
of the importance of large time bandwidth systems fielded in such
designs.
Similar inference is derivable, if one were to think of
frequency agility/waveform coding as an ECCM feature in the same
candidate radar system. Gager5
shows that the relative radar
performance against denial ECM can be summarised to:
Radar
Jammer
R
R
B
P G
r
j
j
j j





 =




























:
P
4
G
S/N L
t t
r
4
2 π
στ
(5.10)
From the above, it becomes clear that the radar's ECCM feature
should force the Jammer bandwidth to be spread out for proper
ECM thrust. This is not a welcome solution for an on-board jammer
with restricted power elements and space. He further shows the
relative merits of different waveforms (with high and low PRF) when
used in the radar transmitter for providing ECCM capability.
Thus, there is clearly a value-added performance index
measurable here. This is both in terms of the quiet range (obtained
through LPI) and the range against jammer (obtained through
application of ECCM). These form a common design solution for the
radar designers.

46
With the advent of phased array solutions, modern radars
are no longer constrained with fixed and non-adaptive antenna
performance. Adaptive antennas provide a welcome feature in the
LPI-ECCM design.
Fleskes6
considers the beam agility in a phased array and
compares the performance of uniform random search with that of
optimised search allocation. The basic search problem usually
encountered is that of finding an allocation of effort in space that
maximises the probability of detection of the target, subject to a
given constraint on the effort. In the example chosen by Fleskes,
the target models are real or the intended ones. However, in the
context of EW, the targets are more likely to be false, elusive and
deceptive. Hence, the search models will have to be cast with certain
stochastic probability figures.
Stone7
and Dobbie8
describe a few such models and relate
how an adaptive or a semi-adaptive solution is possible for arriving
at optimum search frame time. In both cases, the principal
detection function is of the type
b (z) = 1-e [-f (z)]
(5.11)
where f(z) is the search effort function, usually based on the
cumulative probability of detection. This gives diminishing return
for increasing z (effort). The optimal search condition looks for the
appropriate search cells, which increase the posterior detection
probability. The time for search is thus optimally conserved, which
is a LPI function for reducing the time available in space to a
perceived ELINT snooping system.
With an agile, discrete, and adaptive search process
available through electronic scanning, and the possibility of
resolving false targets through ECCM, a feedback loop in the scan
and detection process becomes conceivable. This could be both self-
learning as well as leading to adaptive/optimal search control.
Thus, it becomes feasible to implement an adaptive search scheme
to reduce the mean time to resolve false targets (by association and
with feedback). At the heart of such a system, would be an agile and
adaptive scheme of scan, ECCM, and other resource management,
backed by a processor for online decision9
. The improvement
possible in reducing the depth of penetration of a hostile target is
clearly brought out as a result of adaptive surveillance control. This
emerges again as an intended function of a LPI radar design.
The last model which appears appropriate for consideration
under LPI-ECCM scheme, is the intra-pulse polarisation agile radar

47
(IPAR) proposed by Cohen, et al10
. The IPAR model, as the authors
describe, functions with many unique characteristics. In terms of
LPI, its compatibility with various RF carriers including noise, pulse
compression and polarisation agility can all be cited to its
advantage. The diverse carriers with Doppler-invariant pulse
compression ability, coupled with multi-mode function are good
attributes to radar design for LPI and ECCM functions.
The above models relate the combinational effect of LPI and
ECCM features in a radar design. Such models need to be evaluated
for both functions, preferably at the design stage itself. The
standard EIF definition would need modification from its presently
stated position. As the denial/delay of an ELINT intercept means a
better probability for the victim radar to survive, it is essential that
LPI-ECCM are correlated, and accounted for and evaluated as two
facets of the same entity.
REFERENCES
1. Skolnik, M.I. Introduction to radar systems. McGraw Hill,
1981.
2. Schleher, D.C. Introduction to electronic warfare. Artech
House, 1986.
3. Johnston, S.L. CESM–A new category of radar ECCM. IEEE
Trans. Aerospace Elect. Syst., 1995, 31(2).
4. Wiley, R.G. Electronic intelligence. In The interception of
radar signals. Artech House, 1985.
5. Gager, C.H. The impact of waveform bandwidth upon tactical
radar design. Proceedings of radar, UK, 1982. pp. 278-82.
6. Fleskes, M. Proceedings of radar, UK, 1982. pp. 12-14.
7. Stone, L.D. Theory of optimal search. Academic Press, 1975.
8. Dobbie, J.M. SIAM Jour. Appl. Maths, 1975, 28(1), 72-86.
9. Billetter, D.R. Microwave Journal, 1986, 29(1), 147-57.
10. Cohen, M.N. et al. Proceeding of MSAT-1983. USA.
pp. 483-94.

CHAPTER 6
ECCM IN MULTIFUNCTION RADAR
6.1 INTRODUCTION
Multifunction radar (MFR) design has become necessary
and popular in the present-day environment of air defence for
providing multiple target engagement capability. Such a radar
often combines several functions like search, track, illumination,
guidance, etc., which were handled a few decades back by
separate radars, each having a unique role. Reliability and cost-
effectiveness are added constraints to its operation. The design of
a MFR system is complex as it has to cater for diverse needs;
providing an effective ECCM suite adds another difficult
dimension.
The MFR system is characterised by building many
adaptive designs into it. This starts from the antenna end and
continues through the RF/IF chain, signal processor, data
processor, computer, and finally the display.
In terms of the ECCM modelling for this type of radar,
the following parameters are analysed. These represent typical
modern MFR operating in several countries, deployed usually in
missile air defence complex:
• Phased array antenna with programmable scan/coverage
and sidelobe cancelling system
• Large RF dynamic range receiver with high image rejection
IF system
• Digital signal processing with programmable filters
• Self-contained illumination and guidance system for missiles
• Digital computer system (central as well as distributed) to
cater for various programming controls and processing needs
of the radar

Modelling Radar-ECCM – A System Approach
50
• Encrypted data communication among various components
of the air defence system
- mobile system to centralised command
- radar to missiles and vice-versa
- diagnostics and house-keeping
- multifunction displays with dynamic operator interface.
6.2 MFR ECCM: THE RF CHAIN
In terms of ECCM incorporation, the MFR-RF chain has
many challenges compared to the subsequent digital signal/data
processors:
(a) The entire microwave chain is the first vulnerable hardware
to experience ECM and its effects. It is relatively difficult to
implement/supplement further ECCM features of this chain,
once the design is frozen and its hardware been implemented.
This is largely due to the analog process that is still involved.
Due to the presence of high frequency signals, it is difficult to
get the digital processing scaled up to these ranges. (Present
GaAs technology is being tried to do direct signal processing
at the RF stages but the commercial success has been limited
to regions of ‘L’ and ‘S’ bands so far).
(b) The subsequent signal/data processor, computer and the
video chain, in any case, incorporate many adaptive designs,
thanks to the prevalent, cost-effective culture of digital
technology. Further, what is more important from the ECCM
angle is that these designs are easily and less expensively
adaptable and can render themselves to real-time design
cycles for further improvement and modification to combat
newer ECM threats.
6.3 MFR ANTENNA ECCM
The MFR is characterised by an antenna system
with adaptive scan/beam coverage. Present-day hardware
implementation usually leans towards some form of electronic
scanning: frequency, phase or any number of hybrid types. The
model chosen for further discussion is the phase-phase scan
model. Though limited to sector scan coverage, the phased array
systems ensure the best possible response in high velocity, multi-
target environment, with requisite data rate.
Electronic beamwidth broadening, adaptive/multiple beam
generation, scan coverage tailoring, polarisation control, etc., are
the qualities readily attributed to the phased arrays. High scan

ECCM in Multifunction Radar
51
rates with various dwell rates and some form of adaptive
cancellation to annul interfering signals are the bright ECCM
features which can be derived from the arrays.
Let the present status on these arrays be examined, in
respect of their ECCM response. In basic terms, the phased array
antenna is not a simple or an isolated subgroup of radar.
Electronically speaking, it is no longer possible to separate the
transmitter from the antenna and vice versa. (This is all the more
true with the arrays implemented with the solid state T-R
modules).
The operation of a successful phased array depends on a
number of design variables, along with its evident software
support. The adaptability inherent in the system is a major
consideration for ECCM, but some price has to be paid. The most
serious ECCM limitation in the complex electronic array system
for the MFR is the extent of frequency range of operation.
Multifunction phased array is a poor choice when long-range
search and track functions are integrated into a single radar1
.
Even, combining the properties of a medium-range search radar
with a short-range track function would result in a compromise on
the choice of frequency. When a single phased array is used in this
role, it’s operating frequency and bandwidth are relatively
restricted in that the search and track function should be
accomplished within a single frequency band (S or C band is
normally chosen as the frequency of operation). In the earlier
schemes where separate radars were employed, the frequency
band could extend from L band (for search) to X band or Ka band
(for track). Thus, their radar spectrum occupancy was rather
extended for ECM application.
Another limitation vulnerable to the ECM would be the act
of combining many antennas together in this type of array radar.
Antennas separately functioning for search/acquisition, track,
illumination, guidance, etc., incorporate an inherent set of space-
frequency diversity system among them. This gets compromised
when a compact multifunction system is envisaged and
substituted for. It is hence essential to weigh-in the built-in ECCM
features of a MFR’s segmented aerial coverage against the
erstwhile-distributed deployment background.
The third ECCM consideration for the phased array system
would be on the instantaneous bandwidth and the frequency
range of operations within the chosen band. In the previous

Modelling Radar-ECCM – A System Approach
52
mechanically scanned structures, these did not pose a serious
limitation. Adequate provision in the feed-reflector design
normally took care of the problem. In fact, the limitation in those
radar systems mostly came from the high power transmitter end.
In the present context of phased array, it is observable that limits
to the bandwidth of operations in a frequency band is on a
comparable basis from the transmitter as well as from the phased
array itself. Especially in phase-phase array configuration, the
phase errors and setting accuracy become limiting factors for
wideband operation.
It is then imperative that the question of Broad banding is
emphasised on the array antennas. What then is the position in
this field?
A brief survey2-5
would indicate that the phased arrays
do have theoretical and practical problems peculiar to their type
of scanning. The antenna parameters like beamwidth, gain,
sidelobe, etc., are very much dependent on the scan angle and the
frequency extent of operation. Adaptive nulling and low sidelobe
performances are again variables, which ought to be considered
in relation to scanning programme and the requirement of
bandwidth. In tactical designs, the environment of operation also
plays an important role as the phased array contains a lot of
electronic components.
It is possible to use both amplitude and phase control in a
phased array antenna for synthesis in terms of beamwidth, scan
angle, low sidelobe design, adaptive nulling, etc. At present,
available technology has removed many hardware and system
problems by processing the signals at the microwave frequency for
control/adaptivity, without having to go through a frequency
conversion. Microwave-programmable attenuators, however, are
relatively difficult to realise with a high dynamic range and
sufficient bandwidth6
. Hence, it is the digital, phase-only control/
weighting which is normally employed to obtain the adaptivity in
the phased array, once a given illumination function for the
antenna has been chosen. Thus, the microwave, digital phase
shifters become an important entity of the phased array system.
This is amply evidenced by the amount of work reported in open
literature on this subject.
With phase-only weights, excellent performance has been
reported on phased arrays for low sidelobe control, adaptive
nulling, and null steering; these are important from the ECCM

ECCM in Multifunction Radar
53
angle. How sensitive are these to the demand of frequency extent
of operations and instantaneous bandwidth? Certain comments in
relation to the phase control performance (the most important
element in this scheme) can be cited:
• Quantisation error of digital phase shifter, it’s insertion
phase and phase setting accuracy over the frequency
range, etc., are all functions need to be carefully controlled.
Temperature range of operation is certainly an additional
factor for high power applications and for ferrite phasors.
• Problems of low sidelobe design (for ensuring ECCM) in a
tactical phase-phase steerable array have been addressed7
.
Amplitude and phase setting errors give rise to correlated
and un-correlated errors, and degrade the low sidelobe
performance8
.
• Signal bandwidth decreases with increasing scan angle. For
better performance, subarray steering has to be attempted.
Tight control on phase and amplitude tolerance has to be
exercised on element-on-element and subarray-to-subarray
basis. Such a requirement has been detailed9
in a typical
design, for achieving 50 dB rms sidelobes, using a 5-bit
phase shifter element. It is to be noted that better settable
accuracy and addressability comes with higher bits for the
phase shifter design.
• In coherent sidelobe cancellors, with IQ channels operating,
broadband performance needs complex multipliers with delay
lines10
. Performance degradation in sidelobes, to the tune of
20 dB, is seen if either 6o
of phase or 1 dB of amplitude
mismatch is present between the main and the auxiliary
channels. This factor currently limits the bandwidth of these
adaptive systems. Hence, instantaneous signal bandwidths
are at the moment restricted to around 30 MHz., if high
degree of sidelobe control over frequency is to be
maintained. It is also relevant to point out that there is a
need to implement one channel per jammer in this scheme,
unlike in the adaptive phased array antenna where
simultaneous frequency domain nulling is possible.
6.4 MFR TRANSMITTER ECCM
The transmitter stage of a MFR inherently has a large
number of electronic signatures. It incorporates waveform coding
(in one form or the other) variable pulse length, variable duty ratio

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