Computer engineering dissertation: Robust signal processing techniques for modern gnss receivers

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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.

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Nội dung Text: Computer engineering dissertation: 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. Receiver implementation ............................................................................... 55 2.5. 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. Snapshot GNSS/INS Integration ................................................................. 102 4.6. 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 4fc < 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 generated replica signals that have the time delay from−Tc to Tc with step = 10-2Tc. 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 frequencies (step = 10-1 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 models (step = 10-1 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 diamond dots indicate samples belonging to (k−1)th, kth , and (k+1)th chips, respectively. ............................................................................................................... 54 Figure 2.22: Correlator shapes versus different jitter techniques for GPS L1 C/A signal, where τ runs in the range [−Tc,Tc] with step interval =10−3Tc, 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: 𝑪/𝑵𝟎 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 𝑪/𝑵𝟎 with 𝑷𝒇𝒂 = 𝟏𝟎 − 𝟑 ............................ 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 conditioning-based 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 multi-system 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 𝐮 = [𝑥𝑢 𝑦𝑢 𝑧𝑢 ] and 𝐱 𝑖 = [𝑥 𝑖 𝑦𝑖 𝑧 𝑖 ] be the position of the receiver and of the satellite i. The geometry distance from the receiver to satellite is defined as 𝑟 𝑖 = ||𝐮 − 𝐱 𝑖 ||. Clearly, the vector 𝐮 can be determined if we know the satellite position 𝐱 𝐢 and the distance 𝑟 𝑖 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 𝛿𝑡𝑢 besides 3 unknown elements of 𝒖. With 4 satellites, the equations in these four unknowns are as follows: 18
ρ1 = √(𝑥𝑢 − 𝑥1 )2 + (𝑦𝑢 − 𝑦1 )2 + (𝑧𝑢 − 𝑧1 )2 + 𝑐δ𝑡𝑢 ρ2 = √(𝑥𝑢 − 𝑥 2 )2 + (𝑦𝑢 − 𝑦 2 )2 + (𝑧𝑢 − 𝑧 2 )2 + 𝑐δ𝑡𝑢 (1.1) 3 ρ = √(𝑥𝑢 − 𝑥 3 )2 + (𝑦𝑢 − 𝑦 3 )2 + (𝑧𝑢 − 𝑧 3 )2 + 𝑐δ𝑡𝑢 {ρ4 = √(𝑥𝑢 − 𝑥 4 )2 + (𝑦𝑢 − 𝑦 4 )2 + (𝑧𝑢 − 𝑧 4 )2 + 𝑐δ𝑡𝑢 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 𝒙 = [𝒙𝒖 𝒚𝒖 𝒛𝒖 𝜹𝒕𝒖 ] and using the first order of Taylor expansion as an approximate for every equation as follows: ℎ(𝑥) ≈ ℎ(𝑥0 ) + ℎ′ (𝑥0 )(𝑥 − 𝑥0 ) (1.2) Δ𝜌1 = 𝑎𝑥1 Δ𝑥1 + ax2 Δ𝑦𝑢 + 𝑎𝑧1 Δ𝑧𝑢 + 𝑐Δ𝑡𝑢 Δ𝜌 = 𝑎𝑥1 Δ𝑥1 + ax2 Δ𝑦𝑢 + 𝑎𝑧1 Δ𝑧𝑢 + 𝑐Δ𝑡𝑢 { 2 (1.3) Δ𝜌3 = 𝑎𝑥1 Δ𝑥1 + ax2 Δ𝑦𝑢 + 𝑎𝑧1 Δ𝑧𝑢 + 𝑐Δ𝑡𝑢 Δ𝜌4 = 𝑎𝑥1 Δ𝑥1 + ax2 Δ𝑦𝑢 + 𝑎𝑧1 Δ𝑧𝑢 + 𝑐Δ𝑡𝑢 Δ𝜌1 ax1 ay1 az1 1 Δ𝑥1 Δ𝜌 ax2 ay2 az2 1 Δ𝑥 Let us denote Δ𝜌 = { 2 , H = , and Δ𝑥 = { 2 , Δ𝜌3 ax3 ay3 az3 1 Δ𝑥3 Δ𝜌4 Δ𝑡𝑢 {ax4 ay4 az4 1 then Δ𝜌 = HΔx (1.4) or Δ𝑥 = 𝐻 −1 Δ𝜌 (1.5) If there are more than 4 satellites in view, (1.5) becomes: Δ𝑥 = (𝐻 𝑇 𝐻)−1 𝐻 𝑇 Δ𝜌 (1.6) 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