Nghiên cứu giải pháp nâng cao khả năng chống nhiễu cho các bộ thu định vị GNSS tiên tiến robust signal processing techniques for modern GNSS receivers

MINISTRY OF EDUCATION AND TRAINING
HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY

NGUYEN DINH THUAN

ROBUST SIGNAL PROCESSING TECHNIQUES FOR MODERN
GNSS RECEIVERS

Major: Computer Engineering
Code No.: 9480106

COMPUTER ENGINEERING DISSERTATION

SUPERVISORS:
1. Assoc. Prof. Ta Hai Tung
2. Prof. Letizia Lo Presti

Hanoi - 2019


STATEMENT OF ORIGINALITY AND AUTHENTICITY
I confirm that my dissertation is an original and authentic piece of work written by
myself. The data, results in the thesis is reliable and has never been published by
others. I further confirm that I have fully referenced and acknowledged all material
incorporated as secondary resources in accordance with the regulations
Hanoi,
SUPERVISORS

PHD STUDENT

PGS.TS. Tạ Hải Tùng

Nguyễn Đình Thuận

Prof. Letizia Lo Presti

1


ACKNOWLEDGEMENTS

I would like to express my gratitude to Hanoi University of Technology, Graduate
School, School of Information and Communication Technology, Department of
Computer Engineering and Politecnico di Torino, NavSaS group for creating
favorable conditions for me to work and study.
I would like to express my special thanks to my supervisors, Assoc. Ta Hai Tung
and Prof. Letizia Lo Presti. The supervisors have always been helpful, giving great
advice, scientific orientations so that I can develop and complete my research.
Sincerely thank the lecturers, colleagues in the Department of Computer
Engineering, School of Information and Communication Technology, Hanoi
University of Science and Technology where I work, study and carry out research
projects for the enthusiastic in helping and encouraging me during the research.
With gratitude to teachers, scientists, colleagues and close friends for encouraging
and supporting me in the research process.
Finally, I would like to express my deep gratitude to my family for encouraging me
to overcome all obstacles to complete this thesis.

Nguyen Dinh Thuan

2

TABLE OF CONTENTS
STATEMENT OF ORIGINALITY AND AUTHENTICITY ......................................... 1
ACKNOWLEDGEMENTS ................................................................................................ 2
TABLE OF CONTENTS .................................................................................................... 3
LIST OF ACRONYMS ....................................................................................................... 6
LIST OF TABLES ............................................................................................................... 8
LIST OF FIGURES ............................................................................................................. 9
INTRODUCTION ............................................................................................................. 13
1. FUNDAMENTAL BACKGROUND ....................................................................... 18
1.1. GNSS positioning principle .................................................................................. 18
1.2. History and development of GNSS ...................................................................... 19
1.3. GNSS Threats .......................................................................................................20
1.3.1. Multipath .......................................................................................................21
1.3.2. Atmosphere ....................................................................................................21
1.3.3. Interference ....................................................................................................21
1.3.4. Spoofing ........................................................................................................21
1.3.5. GNSS Segment errors .................................................................................... 21
1.3.6. Cyber Attacks ................................................................................................22
1.4. GNSS Receiver Architecture ................................................................................ 22
1.4.1. Signal Conditioning and Sampling ................................................................ 22
1.4.2. Acquisition ....................................................................................................23
1.4.3. Tracking and Data Demodulation .................................................................23
1.4.4. Positioning Computation ............................................................................... 24
1.5. Countermeasures to GNSS Threats ...................................................................... 25
1.5.1. Antenna array processing techniques ............................................................ 25
1.5.2. Frontend and Digital Signal Conditioning based techniques ........................ 28
1.5.3. Correlator/Tracking and PVT based techniques ............................................ 29
1.6. GNSS Simulator and effect of sampling frequency .............................................. 30
2. GNSS SIGNAL SIMULATOR DESIGN AND IMPLEMENTATION ............... 32

2.1. Modeling methodology ......................................................................................... 32
3


2.2. Overview of the modeling of antenna array signals in GNSS receivers .............. 32
2.2.1. General model of the received signal in GNSS receivers ............................. 33
2.2.2.

Interference ....................................................................................................37

2.2.3.

Multipath .......................................................................................................38

2.2.4.

Noise ..............................................................................................................39

2.3.

Effect of sampling frequency on the positioning performance ............................. 39

2.3.1. Residual code phase estimation ..................................................................... 40
2.3.2.

Correlation output calculation .......................................................................40

2.3.3. Effect of sampling frequency on correlation shape and DLL discriminator
function 42
2.3.4. Effect of the sampling frequency and the integration period selection ......... 42

2.3.5. Effect on the presence of Doppler and local oscillator (LO) clock drift. ...... 45
2.3.6. Theoretical code tracking loop error estimate ............................................... 46
2.3.7. Theoretical results evaluation by simulated, and numerical models ............. 49
2.3.8. Effect of Doppler and coherent integration period ........................................ 50
2.4.

Sampling Frequency Effect Mitigation Technique ............................................... 53

2.4.1.
2.5.

Receiver implementation ...............................................................................55

Performance verification .......................................................................................57

2.5.1. Verification of the simulated antenna array signals ...................................... 58
2.5.2.

Antenna distortion simulation ....................................................................... 64

2.5.3. Verification of multipath simulation ............................................................. 66
2.6.

Conclusion ............................................................................................................67

3. ANTENNA ARRAY PROCESSINGS FOR GNSS RECEIVERS ....................... 69
3.1.

The proposed solution for synchronizing separated antenna array element ......... 69

3.1.1.

Determining the samples difference .............................................................. 70

3.1.2. Determining the clock phase shift ................................................................. 71
3.2.

Implementation a low-cost antenna array ............................................................. 75

3.3.

Antenna array frontend verification ......................................................................76

3.3.1. Phase difference between frontends .............................................................. 76
3.3.2. Carrier to noise ration improvement .............................................................. 77
4


3.4. Conclusion ............................................................................................................ 78
4. GNSS SNAPSHOT PROCESSING TECHNIQUE FOR GNSS RECEIVERS .. 80
4.1.

Proposed Design of GNSS Snapshot Receiver ..................................................... 80

4.1.1.

GNSS Grabber ............................................................................................... 80

Implementation of GNSS Grabber ............................................................................ 80
Firmware Architecture .............................................................................................. 81

4.2. Server Software ..................................................................................................... 81
4.2.1.

GNSS signal acquisition ............................................................................... 81

4.2.2. Combined Doppler and Snapshot Algorithm ............................................. 84
4.3. Loosely coupled Snapshot GNSS/INS ................................................................. 89
4.4.

Tightly coupled Snapshot GNSS/INS ................................................................... 96

4.5.

Results ................................................................................................................... 97

4.5.1. Standalone Snapshot GNSS Receiver ........................................................... 97
4.5.2.
4.6.

Snapshot GNSS/INS Integration ................................................................. 102

Conclusion ..........................................................................................................104

CONCLUSIONS AND FUTURE WORKS .................................................................. 105
PUBLICATIONS ............................................................................................................. 107
REFERENCES ................................................................................................................ 109
APPENDIX ...................................................................................................................... 116
A.

Correlation output calculation ............................................................................ 116

B.

Error analysis for coherent early minus late DLL .............................................. 117

5


LIST OF ACRONYMS
Acronym

Meaning

ADC

Analog to Digital Converter

AGC

Automatic Gain Control

AWGN

Additive White Gaussian Noise

BB

BaseBand

BOC

Binary Offset Carrier

BPSK

Binary Phase Shift Keying

C/A

Coarse/Acquisition

C/N0

Carrier-to-Noise-Density Ratio

CDC

Conventional Differential Combination

CDMA

Code Division Multiple Access

CRC

Cyclic Redundancy Check

CS

Commercial Service

DLL

Delay Lock Loop

DFT

Discrete Fourier Transform

DSP

Digital Signal Processor

EGNOS

European Geostationary Navigation
Overlay Service

EU

European Union

FEC

Forward Error Correction

FFT

Fast Fourier Transform

FPGA

Field Programmable Gate Array

6


FOC

Full Operational Capability

GLONASS

Global Orbiting Navigation Satellite
System

I

Inphase

IF

Intermediate Frequency

Q

Quadrature

PVT

Position Velocity Time

SDR

Software Defined Radio

7


LIST OF TABLES
Table 2.1: GNSS Simulator Features...................................................................................57
Table 2.2: The coordinate of 4 elements..............................................................................58
Table 2.3: The direction of 6 visible satellites.....................................................................59
Table 2.4: The carrier phase relative to the first element of each satellite at the four elements
of the array..................................................................................................................59

Table 2.5: The simulation scenario......................................................................................60
Table 2.6: Estimated carrier phase using the post-correlator beamforming tracking loop .. 62

Table 4.1: Configuration of the GPS grabber.....................................................................97
Table 4.2: Information of acquired satellites...................................................................... 99

8


LIST OF FIGURES
Figure 1.1: Satellite navigation principle.............................................................................18
Figure 1.2: Typical GNSS Threats.......................................................................................20
Figure 1.3: Signal conditioning and sampling stage............................................................22
Figure 1.4: Acquisition Architecture....................................................................................23

Figure 1.5: Tracking Architecture........................................................................................23
Figure 1.6: Transmission time estimation in GNSS receivers............................................. 24
Figure 1.7: Interference mitigation techniques in GNSS receivers..................................... 25
Figure 1.8: The traditional low-cost architecture of antenna array for GNSS applications 27
Figure 1.9: The correlation between 2 GPS signal grabbed by antenna array.....................28
Figure 1.10: Spectrum and histogram of GNSS signal in the absence of interference........28
Figure 1.11: Snapshot positioning architecture............................................................... 29
Figure 2.1: Geometry of antenna array................................................................................33
Figure 2.2: The model of the received signal for a single antenna...................................... 33
Figure 2.3: GPS multi-antenna frontend..............................................................................34
Figure 2.4: Flowchart of the simulator................................................................................ 35
Figure 2.5: Bandlimited Gaussian interference model........................................................ 38
Figure 2.6: Multipath model................................................................................................38
Figure 2.7: Effect of sampling frequency on the positioning performance.........................39
Figure 2.8: Residual code phases versus the number of samples per code chip with 4f c < fs <

5fc................................................................................................................................40
Figure 2.9: Normalised correlator and EML discriminator functions for different sampling
frequencies. Results are obtained by correlating the incoming signal with various local
-2

generated replica signals that have the time delay from−T c to Tc with step = 10 Tc . 42
Figure 2.10: Correlation shapes for 1 ms integration with various sampling frequencies .. 43

Figure 2.11: Ambiguous synchronization between a local PRN code and two different
incoming analog signals of the same PRN sequence, but with slightly differing code
phase offset.................................................................................................................43
Figure 2.12: Correlation shapes and their errors with respect to the ideal correlation at a
sampling frequency fs =16.3676 MHz using various coherent integration periods ... 44
Figure 2.13: Representation of code tracking loop [54]...................................................... 46

9


Figure 2.14: DLL jitter versus different sampling frequencies (step= fc) for a GPS L1 C/A
with C/N0=40 dB-Hz, BL=0.5 Hz, T=1 ms, and fixed BW βr = 2fc............................48
Figure 2.15: Upper bound and lower bound of the DLL jitter versus different sampling
frequencies (step = 5∗10-2 fc) for a GPS L1 C/A with C/N0=45 dB-Hz, BL=0.5 Hz, T=1

ms, and βr = fs.............................................................................................................49
Figure 2.16:

Mean values of two error bounds σs1 and σs2 versus different sampling
-1

frequencies (step = 10 fc) for a GPS L1 C/A with C/N0=45 dB-Hz, BL=0.5 Hz, T=1
ms, and βr = fs.............................................................................................................49
Figure 2.17: DLL tracking error comparison among the simulated, numerical and theoretical
-1

models (step = 10 fc) for a GPS L1 C/A with T=1 ms, and βr = fs...........................50
Figure 2.18: DLL tracking error versus Doppler frequencies fD for different integration
periods T when the sampling frequency is an integer multiple of the nominal code rate
(ns=4), in which the blue dotted lines indicate the typical Doppler range..................51
Figure 2.19: DLL tracking error versus integration periods T. GPS L1 C/A is used with fs =
4.092 MHz (ns=4), C/N0=40 dB-Hz, BL=0.5 Hz, T=1 ms, and βr = fs....................... 52
Figure 2.20: DLL tracking error versus Doppler frequencies fD for different integration
periods T when the sampling frequency is a non-integer multiple of the nominal code
rate.............................................................................................................................. 52
Figure 2.21: Code chip selection versus jitter values with M=4, where Triangle, circle, and

th

th

diamond dots indicate samples belonging to (k−1) , k , and (k+1)th chips,
respectively................................................................................................................. 54
Figure 2.22: Correlator shapes versus different jitter techniques for GPS L1 C/A signal,
−3

where τ runs in the range [−Tc,Tc] with step interval =10 Tc, fs=4.092 MHz, fD = 0
Hz, βr = fs and θNCO(0) = 0.125...................................................................................55
Figure 2.23: Pseudo-code algorithm that can be used to implement jittering solution on SDR
receiver....................................................................................................................... 56

Figure 2.24: The results after applying the mitigation technique........................................ 57
Figure 2.25: Antenna array configuration............................................................................59
Figure 2.26: Post-correlator beamforming receiver architecture [30].................................61
Figure 2.27: Scatter diagram of the tracking output of the satellite PRN01 at 4 elements . 62

Figure 2.28: Estimated position of elements (East-North).................................................. 64
Figure 2.29: Estimated position of elements (Up)...............................................................64
Figure 2.30: Element patterns utilized for simulation (East-North)....................................65
Figure 2.31: The C/N0 of the satellite PRN 1......................................................................65

10


Figure 2.32: Multipath error................................................................................................ 67
Figure 3.1: The architecture of antenna array based GNSS receiver...................................69
Figure 3.2: Time difference between 2 elements................................................................. 71

Figure 3.3: Navigation message...........................................................................................71
Figure 3.4: The architecture of the system to determine the phase offset........................... 72
Figure 3.5: The impact of clock phase shift.........................................................................73
Figure 3.6: The loop filter using for estimating the clock drift............................................74
Figure 3.7: The estimated frequency shift using the loop filter........................................... 74
Figure 3.8: The scatter plot of the signal after mitigating clock phase shift........................75
Figure 3.9: The 3-elements antenna array frontend modified from turner RTL2832Us......76
Figure 3.10: The setup of the verification of the frontend using a GPS simulator..............77
Figure 3.11: Tracking output of satellites in view............................................................... 77
Figure 3.12: / of the satellite PRN 09 for the received signal at every element and

beamed signal............................................................................................................. 78
Figure 4.1: The architecture of the GNSS grabber............................................................80
Figure 4.2: The flowchart of the grabber firmware..........................................................81
Figure 4.3: Acquisition search space.................................................................................82
Figure 4.4: Probability of Detection w.r.t / with
=
−....................................................................84
Figure 4.5: FFT-based acquisition..................................................................................... 84
Figure 4.6: Snapshot solution diagram............................................................................. 88
Figure 4.7: Traditional loosely-coupled GPS/INS integration.............................................90
Figure 4.8: INS mechanization [3].......................................................................................94
Figure 4.9: Tightly-coupled integration scheme..................................................................96
Figure 4.10: The prototype of GNSS grabber....................................................................98
Figure 4.11: Acquisition result of the grabbed signal..........................................................98
Figure 4.12: The position converged after 7 iterations..................................................100
Figure 4.13: The positioning accuracy of the proposed solution..................................101
Figure 4.14: Power consumption comparison of our proposed solution and Ublox LEA 6T
102
Figure 4.15: The experiment setup.................................................................................... 102

11


Figure 4.16: GNSS Snapshot/INS integration result......................................................... 103
Figure 4.17: Positioning performance between GNSS Snapshot and GNSS Snapshot/INS
Integration.................................................................................................................103

12


INTRODUCTION
Nowadays, GNSS receivers have become core components in many applications ranging
from vehicle navigation to unmanned vehicle guidance, from location-based services to
environment monitoring. Besides providing position information for many applications,
GNSS services also provide a highly precise timescale for synchronizing systems such as
telecommunication and network. Hence, the performance of GNSS which have
considerable influence on the operation of these services must be guaranteed. In [1] a list of
four parameters of GNSS performance is reported: accuracy, availability, continuity, and
integrity. Recently, the accuracy of GNSS has been significantly improved with the
development of new navigation systems (Galileo-European system and BEIDOU-Chinese
system) and the modernization of the existing navigation systems GPS and GLONASS.
However, GNSS services are seriously being threatened by the emergence of jamming and
spoofing threats.
Because GNSS signals are buried under ambient noise, the signals and services of GNSS
systems are highly sensitive to interference such as radio frequency interference, jamming
and spoofing; meanwhile, the quality of such services is not guaranteed to the conventional
users. Technically, the GNSS signal is transmitted from satellites away from Earth (about
20.000 km), so when it comes to receivers, the signal power is smaller than the background
noise about 1024 times (26dB) [2]. Therefore, any source of interference (jammer, digital

terrestrial communication systems, ionosphere scintillation) may reduce the quality of the
received signal, which in turn can disable the operation of the receiver. In addition, because
the GNSS systems are often under the management of military based organizations [3] [4]
[5], the open services (e.g., GPS L1 C/A, Beidou B1, GLONASS L1OF) are provided to
users without any guarantee of their reliability and continuity. However, ensuring reliable
and continuous position and time information is essential in modern GNSS receivers. To
meet these requirements, receivers must make use of advanced techniques to detect and
mitigate interferences so that they can provide the requested continuous position and time
information. These techniques are called “interference mitigation techniques”.
In recent studies [6] [7] reflecting the state of the art, interference mitigation techniques
can be classified according to the position of the algorithm within the processing stages of
GNSS receiver chain. In short, they are classified into three groups namely antenna array
processing techniques, frontend and digital signal conditioning-based techniques, and
correlator/tracking and PVT based techniques
Antenna array signal processing technique: A popular method for robust GNSS receiver
performance consists in using multiple physical antenna elements which constitute a so-called
antenna array. This technique has been studied since the 1940’s and has been widely used in
radar and telecommunications applications [8] [9] [10] [11]. Recent studies exploited this
technique for GNSS applications considering it as an effective method to mitigate

13


interference. However, conventional antenna array-based processing leads to complicated
and expensive systems, and it is not suitable for mobile receivers [12] [13] [14]. Although
there are several efforts to design low-cost antenna array for GNSS applications [9] [10],
issues involved to the implementation in a GNSS receiver still exist. While 2 bits of
quantization in ADC, have been proved to be enough for GNSS receivers [15], however it
makes the GNSS receivers less robust to threats due to the saturation of the ADC against
the high power of the interference. Also, expanding the number of antenna elements is a

challenge due to the limited interface bandwidth. To overcome those limitations, the signal
from elements can be independently grabbed first and then their signals are synchronized.
In this approach, synchronization becomes the vital process to be performed before
combining the signals from the array. Thus, the design of robust calibration algorithms that
corrects for the time, phase and frequency mismatch among array data becomes a
necessity. To estimate the phase difference between elements, we can use least squares and
maximum likelihood such as [16] [17]. Phase calibration of antenna arrays can also use the
live-sky GNSS signal [18] [11]. Regarding time offset estimation, there are some studies in
telecommunication field which address the issue using the correlation technique [41] [42].
However, those studies assume that the power of the interested signal is much higher than
ambient noise. Therefore, the assumption may not hold true when GNSS signals are
involved.
Frontend and Digital Signal Conditioning based techniques: In this second group of
interference mitigation techniques, some unusual properties of interference signals such as high
power, spectrum shape, raw sample distributions are used for interference detection. While [19]
proposed the use of AGC to detect jamming signal, [15] uses this information to detect a
spoofing repeater. Although this is considered as a promising technique in detecting jamming
and simplistic spoofing, the information needed for its implementation is not always available
in commercial frontends. On top of this, for what concerns the application to spoofing
detection, since this technique observes the sudden change in the receiver power, it is useful
only if it monitors the signal before the occurrence of a spoofing attack. In more complicated
spoofing scenarios, the technique cannot differentiate the spoofed signal from the real signals
because the spoofed signals are mimicking the properties of the authentic signals. While the
frontend-based techniques are only for interference detection, the digital signal conditioningbased techniques are useful in minimizing the effect of interference. Among the techniques of
this second group, pulse blanker and notch filter have shown that they can improve several dB
after jamming mitigation [20] [21]. However, as mentioned above, this technique cannot apply
to spoofing mitigation because spoofing signal properties are analogous to those of authentic
signals.

Correlator/Tracking and PVT based techniques: Like the second group of interference

mitigation techniques, these techniques rely on the detection of abnormal outputs in
correlator or PVT in order to identify the presence of interference. Take C/N0 monitoring

14


technique as an example. This technique is based on the abnormal power of the
interference. However, it uses the carrier to noise ratio information instead of absolute
received signal power using in the second group of interference mitigation techniques. In
PVT based techniques, the consistent check or cross check will guarantee the reliable
information in PVT stages (i.e., pseudorange, ephemeris data). A typical technique in this
group is Receiver Autonomous Integrity Monitoring (RAIM). Although it is proved to be
effective to detect failures in pseudorange measurement [22] [23], the measurement is
available only if the tracking stage is without loss of lock. The requirement cannot be
guaranteed under powerful jamming attack which aims to cause the receiver complete loss
of lock. Therefore, to guarantee the availability of a PVT solution, recent studies have
suggested to adopt a coarse time positioning solution for coping with environments
affected by interference. It is considered as an efficient method that can be applied to an
area where the continuous GNSS signal tracking is not guaranteed due to interference [24]
[25]. Compared to traditional receiver, the positioning performance of this technique is less
precise. Recent studies have been improving its positioning performance on the GPS L1
snapshot receiver [26] [27] [28] but the use of multi-constellation and INS integration in
snapshot receiver has not been explored sufficiently in previous works.
Another difficulty during the design and implementation of interference mitigation techniques
is the performance evaluation and verification process. Currently, these processes can be done
using either live-sky GNSS signal [29] or GNSS simulator signal [30]. The first approach is
straightforward to implement, but it is difficult to control the environments along with GNSS
signals. Therefore, the latter is the method being used favorite now. However, there are existing
limitations with the use of GNSS simulators available in the market for SDR based study.
Because the input data of the study is the digitalized IF signal, in order to grab such kind of

data we need to use a grabber frontend which may include unavoidable errors, moreover, the
performance of the SDR based receiver are strongly affected by the sampling frequency so the
chosen value should be considered carefully during simulation.

Motivation
From the above analysis, advanced processing techniques for resilient positioning and
timing are essential in modern GNSS receivers. Therefore, goal of this work is to propose
techniques to overcome the existing limitations in antenna array processing and snapshot
processing for modern GNSS receivers. The proposed techniques not only reduce the
implementation cost but also leverage the distributed data processing ability.
Scope of Research
The work mainly focusses on antenna array processing technique and snapshot technique
for modern multi-GNSS receivers. While the first technique enables designing and
implementing a low-cost antenna array for GNSS applications, the second technique can
provide reliable position and time information in strongly interfered environment. Remark

15


also that all the simulations through the dissertation are performed with the data generated
from a software-based GNSS simulator. The design and implementation of this simulator
are also part of this thesis. The approach to these techniques is based on SDR technology
where the signal processing chains are implemented by means of software on a personal
computer before deploying to the FPGA.
Methodology
For this study, the following approach is adopted. First, relevant literature and studies are
reviewed to get in-depth knowledge of interference mitigation techniques. Also, the
processing chains in GNSS receivers (i.e., acquisition, tracking and PVT computation) are
reviewed. Second, solutions are proposed to address the existing issues in the
implementation of modern GNSS receivers. Finally, the obtained result is analyzed,

processed and checked against information obtained from literature and previous studies.
Contribution
As mentioned above, the study focuses on proposing solutions to address the two main
issues: the use of low-cost antenna array to detect GNSS threats and the use of multi-GNSS
snapshot positioning technique for discontinuous GNSS signal environment.
Regarding antenna array signal processing technique, the work has proposed the
synchronization mechanism that enables the use of low-cost antenna array processing in
GNSS field. Theoretical and empirical results show that this is a promising solution that
will not only reduce deployment costs but also be a flexible solution for expanding the
number of antenna elements.
As for the second issue addressed, the thesis proposes an integrated model of a multisystem snapshot receiver with an inertial positioning system (INS). Theoretical and
experimental results have shown the superiority of performance of this solution over the
use of solutions exploiting only single GNSS systems. This integrated model is particularly
suitable for environments where GNSS signals are intermittent.
The results presented in this thesis have been published in 6 conferences and 5 journals as
listed in the attachment. The works have been carried on at Hanoi University of Science
and Technology (Vietnam) and at Politecnico di Torino (Italy).
Thesis outline
The thesis is organized in 4 chapters as follows:
Chapter 1 – Fundamental Background: In this chapter, the background knowledge related
to the stages of GNSS receiver architecture including acquisition, tracking and data
demodulation, and position computation are revised. Also, this chapter show state of the art
of the interference mitigation techniques. The limitations of existing works in the

16


implementation of antenna array frontend and snapshot positioning technique are also
carefully considered.
Chapter 2 - GNSS Signal Simulator Design and Implementation: In this chapter, the

design, and implementation of a GNSS software-based simulator are carefully considered.
As one of the most critical parameters related to the speed of signal generation, the effect
of sampling frequency is also generalized theoretically in both simulator and receiver sides.
Chapter 3 – Antenna Array Signal Processing for GNSS Receivers: This chapter focuses on
a solution enabling the extension of the number of elements and the quantization bits. It is
applied in a low-cost antenna array for detecting the source of spoofing and interference.
Chapter 4 – Snapshot Signal Processing for GNSS Receivers: This chapter shows how the
multi-constellation snapshot technique can be effectively implemented. In addition, to
improve positioning performance, the snapshot GNSS/INS integration is proposed.

17


CHAPTER 1

1. FUNDAMENTAL BACKGROUND
This chapter provides the overview of relevant theory for the thesis. As pointed out in the
previous sections, the thesis mainly focuses on the array processing and Snapshot
positioning for modern GNSS receivers under threats. Therefore, this chapter first provides
the principle of GNSS positioning and history and development of existing GNSSes. Then,
the brief introduction of emerging threats is provided. Finally, the processing chains in
GNSS receivers are fully described.

1.1. GNSS positioning principle
This section will explain the general principle of GNSS navigation. Basically, GNSS
positioning is based on trilateration techniques. In this technique, the receiver firstly
determines the distance from its position to at least three known points. After that, the
receiver’s position is determined by the intersection of 3 spheres (Figure 1.1)

Figure 1.1: Satellite navigation principle

Let = [ ] and = [ ] be the position of the receiver and of the satellite i. The geometry distance from the receiver to satellite is defined as = || −
||. Clearly, the vector can be determined if we know the satellite position and the distance

with i=1,2,3.
In GNSS receivers, the distance cannot be measured directly but it uses the transmission
time from satellite to receiver. Unfortunately, the receiver clock is not synchronized with
the atomic clocks onboard of GNSS satellites. As a result, we have one more unknown
variable besides 3 unknown elements of . With 4 satellites, the equations in these four
unknowns are as follows:

18


ρ1
= √(

−

1 2

−

1 2

− 1 )2 + δ

ρ2

= √(

−

2 2

−

2 2

− 2 )2 + δ

ρ3

= √(

−

3 2

−

3 2

− 3 )2 + δ

{ρ 4

= √(

−

4 2

−

4 2

− 4 )2 + δ

) +(

) +(

) +(

) +(

) +(

) +(

) +(

) +(

(1.1)

where c is the speed of light.
When considering the other errors (e.g., ionospheric, tropospheric), we have the complete
form of the equations [31]
Denote vector solution = [ ] and using the first order of Taylor expansion as an approximate for every equation as follows:

′
ℎ( ) ≈ ℎ( 0) + ℎ ( 0)( − 0)

(1.2)
Δ

1

=

1Δ 1

+ ax2Δ +

1Δ
1Δ

+ Δ {Δ 2 = 1Δ 1 + ax2Δ + 1Δ + Δ Δ
+ Δ Δ 4 = 1Δ 1 + ax2Δ + 1Δ + Δ

Δ

a

1

,

Δ

Let us denote Δ = {

2

a

x2

Δ

a

y1

z1

3

=

1Δ 1

a

1

a

a

1

y2

z2

+ ax2Δ +

1

a

H=

Δ

1

,

Δ

, and Δ = {
a

Δ

a

x1

3

x3

y3

z3

2

Δ

1

(1.3)

3

Δ

4

a
{ x4

a

a

y4

z4

then

(1.4)
Δ = HΔx

or
(1.5)
Δ =

−1

Δ

If there are more than 4 satellites in view, (1.5) becomes:
(1.6)
)

−1

Δ

Δ =(

1.2. History and development of GNSS
The first GNSS is the Global Positioning System (GPS). The project was approved by the
United States Department of Defense in 1973. When the system was fully operational in

1995, its constellation consisted of 24 satellites spreading in 6 orbit planes. The current

19


operational constellation is made up of 30 satellites. GPS signal frequencies are allocated
in three bands: L1 (1575.42 MHz), L2 (1227.6 MHz), and L5(1176.45 MHz) [3].
Also in 1970s, Russia developed its own navigation satellite system called GLObal’naya
NAvigatsionnaya Sputnikovaya Sistema (GLONASS). It was designed to have 24 satellites
in 3 orbit planes. At the time of writing, there were 29 satellites but only 24 satellites were
operational. The GLONASS signals are transmitted on G1 (1598.0625 – 1605.375 MHz),
G2 (1242.9375 – 1248.625 MHz), and G3 (1201.5 MHz) bands [4].
With the objective of being the first civilian GNSS, Galileo project was approved by
European Space Agency in 2002. When fully deployed, the system will consist of 27
operational and 3 spares satellites in 3 circular Medium Earth Orbit (MEO). Galileo signals
are transmitted in 4 frequency bands: E1 (1575.42MHz), E5 (1191.795 MHz), E5a
(1176.45 MHz), E5b (1207.14 MHz) and E6 (1276.75 MHz) [32].
In 2000, China launched the first satellite of Chinese satellite navigation system (Beidou1). The coverage of the system was limited to China and neighboring regions. The second
generation Beidou system became operational in 2011 with 10 satellites in orbit. It is
designed to have 5 geostationary Earth Orbit (GEO) satellites, 27 Medium Earth Orbit
(MEO) satellites, and 3 inclined geosynchronous satellite orbit (IGSO) satellites. The
Beidou signals are transmitted in three bands: B1 (1559.052 – 1591.788 MHz), B2
(1166.22 – 1217.37 MHz), and B3 (1250.618 – 1286.423 MHz) [4].

1.3. GNSS Threats
To operate GNSS services in a reliable way, understanding the growing threats to satellite
navigation signals is essential. Since the signal power is extremely weak, GNSS signals
can easily be disrupted by emerging threats which can be divided into 2 categories: natural
(i.e., multipath and atmosphere) and man-made threats (interference, spoofing, GNSS
segment errors, and cyber-attacks) [33] (see Figure 1.2).

Figure 1.2: Typical GNSS Threats

20


1.3.1. Multipath
The error is well-known and is source of problems not only in GNSS but also in the radio
telecommunication field. It is caused by reflection: the GNSS signals are reflected by high
building or objects and cause large error if the receiver tracks the reflected signal instead of
the line-of-sight signal. Multipath is one of the most significant challenges amongst natural
threats and can cause errors of several to hundreds of meters in positioning performance.
1.3.2. Atmosphere
Before reaching GNSS receivers, GNSS signals must pass through the atmosphere with all
its variations. While the troposphere layer only causes small changes in signal phase and
amplitude, the ionosphere causes more serious errors, particularly during periods of intense
solar activity. Perturbation in the ionosphere around the equator and the two poles, which is
the so-called scintillation - can cause GNSS signal disruptions or very rapid changes in
phase and amplitude of the signal. Thus, a GNSS receiver will be loss of lock if it has not a
robust engine.
1.3.3. Interference
The simplest form of jamming consists in transmitting a specific signal or noise to cause
GNSS receiver overload or loss of lock. The attack is sometimes unintentional. High power
harmonics from radar systems, TV radios, VHFs, mobile satellite services and personal
electronics can inadvertently interfere with the GNSS signal.
Recently, with the advent of hand-held GNSS jammers, GNSS signals within a radius of a
some tens of meters are completely disrupted. The operating principle of these devices is to
use a chirp signal to intervene in the operating frequency range of the GNSS signal. There
are currently no effective methods to minimize the impact of this type of attack
1.3.4. Spoofing

GNSS spoofing is a kind of attack that deceives a GNSS receiver by transmitting a fake GNSS
signal with false information or by transmitting the genuine signal grabbed elsewhere or at
another time. These counterfeit signals modify the navigation message and code phase in such
a way that the receiver estimates its position somewhere else than in its actual position, or in
the correct position but at another time. A common form of GNSS spoofing attacks begins
broadcasting signals synchronized with the genuine signals. The power of the counterfeit signal
is then gradually increased to dominate the genuine signal. As a result, the GNSS receiver
cannot realize the change and completely tracks the counterfeit signals.

1.3.5. GNSS Segment errors
The GNSS system can fail even without human intervention. The satellite onboard atomic
st

clocks sometimes generates cumulative errors before informing users. On 1 January 2004,
the error on GPS SVN-23 satellite caused a range error of up to 300 km.

21


An error in signal modulation or generating process can also lead to errors in positioning
performance of the receiver. In 1993, the evil waveform from GPS PRN 9 caused 8 meters
in pseudorange error.
1.3.6. Cyber Attacks
Unlike other forms of attacks, this attack is related to manipulation of the software layer in
devices to change the position information. There is evidence that the attack is used in the
maritime segment with Automatic Identification System (AIS) data manipulation.

1.4. GNSS Receiver Architecture
1.4.1. Signal Conditioning and Sampling
The architecture of the signal conditioning and sampling is illustrated as in Figure 1.3

In this stage, the received signal is conditioned to meet the requirement of the sampling
process. For simplicity, consider the GPS L1 signal from a satellite:
( ) = √2 ( − ) ( − )cos(2

(1.7)

+ )

where is the received power of the GPS L1 signal. ( ) and ( ) denotes the code and data of the consdired satellite.

After the mixer, the received signal is separated into I and Q component. Without loss of
generality, from now on, we will use the complex signal to represent the signal on I and Q
channel. The signal after mixer is:
( ̂ ) = √ ̂ ( − ) ( − )

+ ̂))

( (2

(1.8)
+ √ ̂ ( − ) ( − )

( (2 (2

1

+

) + ̂))

Figure 1.3: Signal conditioning and sampling stage

22


1.4.2.

Acquisition

The acquisition stage is aimed to roughly estimate the code phase and Doppler shift of
visible GNSS satellites. In fact, the stage performs correlation with every Doppler
frequency and code phase bin in the search space (Figure 1.4). A satellite is considered as
visible if there is the value of a cell in the search space higher than a specified threshold.
The code and frequency corresponding to the cell is the output of the acquisition. The
selected threshold must be considered carefully because it is related to the number of
satellite in use that is proportional to the accuracy of the solution.
x[n]
FFT

IFFT

|.|

2

(.)

*j
()*

90

FFT
Carrier
NCO

Non-

Code NCO
FFT-based Acquisition

coherent

Integration

Figure 1.4: Acquisition Architecture

1.4.3. Tracking and Data Demodulation
After the acquisition, the receiver has roughly code phase and Doppler frequency of every
satellite in view. However, those parameters are changing over time due to the change of
the relative position between the satellite and receiver. The tracking stage is aimed to keep
track the replica local code and carrier and the received signal with the Delay Lock Loop
(DLL) and Phase Lock Loop (PLL)

Figure 1.5: Tracking Architecture

23


Similar to acquisition stage it performs mixing the received signal with the replica code and

carrier. The PLL wipes off the carrier [31] and the DLL align the local and incoming PRN
codes. The signal after the direct digital frequency synthesizer (DDFS) is down-converted to
baseband and is ideally contained in only the in-phase (I) channel. The DLL tracks the time
delay of the incoming PRN. The baseband signal is correlated with 3 local replica code-taps:
Early (E), Prompt (P), and Late (L), through multiplication and integration, usually over an
integer PRN code period (T0). Discriminator feedbacks adjust the Code NCO, which fluctuates
the local replica code rate to synchronize with the incoming code [34]

1.4.4. Positioning Computation
Positioning computation is performed with the assumption that the received signal is
acquired and tracked successfully from a minimum of four satellites in view. After
navigation message demodulation, the receiver can determine the received time and the
position of all satellites in view. To apply (1.1), the receiver needs to measure the distance
from the receiver to all satellites. In GNSS receivers, the quantity cannot be directly
calculated but it is derived through the transmission time. It is worthy to note that the
convergence solution of (1.6) will not change if a constant value is added to all
pseudoranges. Therefore, the receiver will calculate the difference between transmission
time instead of the absolute value. The differences are computed by counting the number of
sample intervals since the receiver started to the preamble bits in the same subframe for all
satellites (Figure 1.6).

Figure 1.6: Transmission time estimation in GNSS receivers

24