1. Flexible Hardware Implementation of Collaborative
GNSS Tracking Channel
Heikki Hurskainen, Jussi Raasakka, and Jari Nurmi
Department of Computer Systems
Tampere University of Technology
Tampere, Finland
Email: firstname.lastname@tut.fi
Abstract—The most of the upcoming global satellite naviga- implementation results with analysis of the complexity of our
tion system (GNSS) signals will be composite type. Composite architecture. The paper is organized as following; the future
satellite signals have unique spreading codes both for data composite GNSS signals and collaborative tracking algorithms
channel and dataless (pilot) channel. The combination allows
both data extraction for navigation and longer integration of are discussed in Section II, the TUTGNSS receiver and a novel
pilot for better timing and thus positioning accuracy. The non- implementation of composite tracking structure are presented
coherent and coherent collaborative tracking algorithms are in Section III. Finally the implementation results are presented
presented in literature. In this paper we present our work on in Section IV.
flexible hardware implementation, capable for both types of
collaborative tracking. The implementation is done with FPGA
based TUTGNSS receiver platform, and synthesis results for II. F UNDAMENTALS OF COLLABORATIVE SIGNAL
implementation are presented. From results it can be seen that the TRACKING
logic consumption overhead for 16-channel collaborative tracking
unit is 56.9% with full hardware support and 26.6% with A. Composite satellite signals
optimized hardware support when compared to design without Optimal dual frequency combination for low cost
the presented structure.
GPS/Galileo was outlined in our earlier work [3], thus in this
paper we discuss only signals within that frequency selection.
I. I NTRODUCTION
Both modernized GPS and Galileo will deploy composite
Global Navigation Satellite Systems (GNSSs) are entering signals. The modernized GPS L1C signal, to be transmitted in
a new era. The U.S. based NAVSTAR Global Positioning L1 frequency band (centered at 1,575.42 MHz), is using binary
System (referred as GPS), with its modernization plans, is offset carrier (BOC) modulation on data channel ������1������������ and
still the main system used, but it is about to be facing both time multiplexed BOC (TMBOC) modulation on pilot channel
competition and completion from European Galileo system. ������1������������ [4]. Both channels are using their own sets of spreading,
Both modernized GPS and Galileo are introducing new com- or pseudorandom noise (PRN) codes. The transmission power
posite signals where the traditional data channel, consisting of of the channels is weighted (25%/75% between data and
low rate navigation data, spreading code, possible modulation pilot) to meet the power spectral density (PSD) criteria of
signal and carrier wave is enhanced with a pilot channel. multiplexed BOC (MBOC), which is set by the agreement
Pilot signals do not contain any navigation data, only a between European and U.S. GNSS authorities to ensure the
short secondary code. The benefits of having composite signal compatibility of satellite navigation systems [5]. In the new
comes from the dispersion of the two main properties of GNSS frequency band centered at 1176.45 MHz, GPS L5 signal is
signal; navigation data and timing information. While the data the first real navigation signal deploying composite signal. The
channel holds the data containing ephemeris and almanac composite L5 signal consists of data component transmitted in
information of the satellite constellation, the pilot channel in-phase and pilot channel transmitted in quadrature phase, and
can be integrated over longer periods to enhance the carrier- the code is binary phase shift keying (BPSK) modulated on
to-noise ratio of the received signals. Naturally, the receiver the carrier [6].
should be able to cope with the new composite signals, and Galileo signals, sharing the aforementioned frequency
the research over this area has been active. New algorithms bands, are called E1 and E5a. Both signals are composite
for both composite acquisition [1] and tracking [2] have been type, differences being in the modulation type and spreading
presented in last years. code used and data rates. The biggest difference between
In this paper we present our work towards the implementa- the signal fundamentals is the selected method of PRN code
tion of flexible hardware architecture for collaborative tracking creation. The E5a spreading codes are generatable, much like
of composite GNSS signals. The hardware capable of track- in equivalent GPS L5 signal, whereas E1 signal is using
ing all composite signals is implemented in our TUTGNSS memory codes, impossible to generate without an error [7].
receiver, a university based receiver tool running on Field Thus, shared code memory is needed to enable replica code
Programmable Gate Array (FPGA) platform. We present the reproduction in tracking channels. The main properties of
978-1-4244-8971-8/10$26.00 c 2010 IEEE

2. TABLE I
C OMPARISON OF COMPOSITE GPS AND G ALILEO SIGNALS IN SHARED
FREQUENCY BANDS
Signal Data rate [Hz] PRN rate [MHz] Modulation
GPS L1C 100 1.023 TMBOC
GPS L5 50 10.230 BPSK
Galileo E1 250 1.023 CBOC
Galileo E5a 50 10.230 BPSK
composite GPS and Galileo signals of interest are summarized
in Table I.
B. Collaborative Tracking Algorithms
Tracking is one of the key processes in satellite navigation
receivers. The signals transmitted by satellites are below noise
floor when entering the surface of Earth. Spreading codes
are used in transmitted signals, and when correlated to a
local replica with correct code delay and Doppler frequency
information, the integrated result raises signal power above
noise and thus data becomes readable. Acquisition is a process
to find the coarse values for code delay and Doppler frequency.
When found, tracking is used to fine-tune these values and
to decode the navigation data from the received stream [8]. Fig. 1. Non-coherent channel combining
Collaborative (or sometimes composite) tracking refers to
cooperative tracking of both data and pilot channels, and is
discussed with detail in [2]. This approach combines the best
of both worlds, tracking data channel enables navigation data ������ = (������ + − ������+ )������������ + (������ − − ������− )(1 − ������������)
extraction, whereas tracking pilot channel enables long inte- 1
gration, independent of navigation bit boundaries, to estimate = √ [(������������ + ������������������ ) − (������������ + ������������������ )]������������ (2)
2
the exact timing of the signal. 1
Non-coherent collaborative code tracking is illustrated in + √ [(������������ + ������������������ ) − (−������������ + ������������������ )](1 − ������������)
2
Figure 1. There incoming signal is correlated with multiple
correlators in two parallel channels, correlation results are where ������������ = 1 if ∣������ + − ������+ ∣ > ∣������ − − ������− ∣ and ������������ =
integrated and fed to discriminator computation. The number 0 if ∣������ + − ������+ ∣ < ∣������ − − ������− ∣. The analysis presented in
of correlators used per channel has a close relation to the [2] shows that coherent channel combining outperforms non-
tracking algorithm used, e.g. typical discriminators for a single coherent algorithms.
channel tracking consume three (e.g. narrow early-minus-late III. I MPLEMENTATION OF C OLLABORATIVE S IGNAL
correlator (NEML) [9]) to five (e.g. high resolution correlator T RACKING
(HRC) [10]) correlators. Discriminator output ������ is filtered and
used to control the frequency of replica code generation. The A. TUTGNSS
composite discriminator for non-coherent channel combining The fully university based TUTGNSS receiver is currently
is given in Equation 1 [2]. running on Altera Stratix II FPGA platform [11]. The whole
design consists of i) third party radio frequency front end (RF-
������ = (∣������������ ∣2 + ∣������������ ∣2 − ∣������������ ∣2 − ∣������������ ∣2 ) (1) FE), ii) modular hardware design written in VHDL and iii)
softcore NiosII processor [12] running the necessary baseband
Where ������ denotes correlation result for early and ������ for late control and navigation software. The RE-FE is attached to
correlator, results achieved both from data ������ and pilot ������ (upper the expansion interface of the FPGA through an additional
and lower channel in Figure 1 respectively). interface PCB and the navigation output as well as baseband
Figure 2 illustrates the coherent channel combining. In debugging information are accessible through serial interface
coherent tracking both channels use composite signal replicas, (RS-232) and serial peripheral interface (SPI) respectively
difference being in relative sign between data and pilot com- [13].
ponents. There exists relative sign ambiguity due to the data The hardware is implemented with modular approach,
bit modulated in data signal, thus both variants are tracked and where the main design is hierarchically constructed from
maximum function is used to select the correct discriminator different functional units (e.g. Acquisition Unit, Tracking
result. The discriminator for coherent early minus late channel Unit), thus allowing change or modification of one unit without
combining can be expressed as: modifying the others. The top level hierarchy of TUTGNSS

3. Fig. 3. Top level of TUTGNSS hardware
TABLE II
F ULL MASTER – SLAVE INTERFACE
Fig. 2. Coherent channel combining Signal Width Description
sv select 16 signal selection register
sv special 16 special register
hardware is illustrated in Figure 3. Baseband converter unit code nco 32 Code NCO increment
carrier nco 32 Carrier NCO increment
(BCU) interfaces with RF-FE, and converts the incoming dig- start sc 32 Tracking time
ital RF stream to more compatible with the rest of the system. ctrl 32 Channel control
Master control unit (MCU) is interfacing the Nios II CPU with
the rest of the hardware accelerator. Acquisition unit (AU)
encloses one massive parallel acquisition structure, whereas channel contains a dedicated memory handler for reading the
tracking unit (TU) contains 16 flexible tracking channels, each 32-bit blocks of PRN code from the shared code memory.
channel containing up to 8 correlators. Phase measurement BOC modulation is added to PRN code in the tracking
unit (PMU) and tracking result unit (TRU) are acting as channel, where the spreading code chip is simply XORed with
intermediate storages for tracking channel measurement and the most significant bit of NCO register to result BOC(1,1)
output data. Sample counter unit (SCU) creates the internal modulation.
time reference for the receiver.
C. Master–Slave Channel Structure
In our receiver, the hardware performs mainly the corre-
lation functions for acquisition and tracking. The units read The composite tracking is enabled in TUTGNSS by intro-
their controls from dedicated control registers and similarly ducing a master–slave structure. Tracking channels have alter-
write their results to result registers. Control software uses the native control input from multiplexer structure (as illustrated
same registers to read results and write feedback to operations in Figure 4). All channels are capable of performing in both
(e.g. tracking loops). In this way there are no decision making master and slave modes, the mode is controlled by control
mechanisms implemented in hardware, only the necessary signal.
hardware acceleration is implemented. TUTGNSS software is ∙ In master mode the channel operates as normal, the
also designed with modular approach, and it can be roughly tracking is controlled by software via MCU.
divided to baseband control and navigation processes. The ∙ In slave mode the channel operates as a slave to an-
latest status of the navigation software is presented in [14]. other (master) channel, in this mode the tracking process
control inputs, listed in Table II, are read from master
B. Flexible Tracking Channel channel. Master channel can be any of the remaining 15
The concept for flexible tracking channel was introduced in channels and the selection is controlled also through ctrl
our earlier work [3]. The target in flexible channel design has register. The PRN number is bitmasked to produce pilot
been on maximal hardware re-usage for tracking of different code when the master is tracking data and vice versa.
signals, only signal specific blocks (e.g. code generators) have This arrangement enables flexible configuration of collabo-
been added with multiplexers. Shared memory for Galileo E1 rative tracking on-the-fly, independent of the current usage of
codes is implemented outside of the tracking channels. Each channels. It also enables efficient and flexible usage of mixed

4. TABLE III
R ESOURCE C ONSUMPTION OF 16– CHANNEL DESIGN (T RACKING U NIT
ONLY ) IN A LTERA EP2S180F1020C3 D EVICE
Design Combinatorial ALUTs Platform resources
w/o master–slave 18,335 12.8%
master–slave full 28,769 20.0%
master–slave opt 23,203 16.2%
maintaining the flexibility and reconfigurability needed from
future receivers. The tracking channels were implemented on
TUTGNSS receiver platform and the hardware complexity was
evaluated with synthesis results. The results showed 59.6%
increase in logic consumption, when a 16-channel design
with full master–slave structure was synthesized. With design
optimization the increase in hardware overhead was reduced
Fig. 4. Implemented master–slave structure of TUTGNSS tracking channels
to 26.6%.
ACKNOWLEDGMENT
modes of single channel (e.g. for legacy GPS C/A signal) and The research leading to these results has received funding
dual channel (collaborative) tracking, since no hardware has from the European Union’s Seventh Framework Programme
been cemented to work in a single mode. (FP7/2007-2013) under grant agreement n∘ 227890 (GRAM-
The TUTGNSS channels are capable of creating only binary MAR project).
replicas, thus composite replica code creation in case of
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