Efficient Delay Tracking Methods with Sidelobes Cancellation for BOC-Modulated Signals

In positioning applications, where the line of sight (LOS) is needed with high accuracy, the accurate delay estimation is an important task. The new satellite-based positioning systems, such as Galileo and modernized GPS, will use a new modulation type, that is, the binary offset carrier (BOC) modulation. This type of modulation creates multiple peaks (ambiguities) in the envelope of the correlation function, and thus triggers new challenges in the delay-frequency acquisition and tracking stages. Moreover, the properties of BOC-modulated signals are yet not well studied in the context of fading multipath channels. In this paper, sidelobe cancellation techniques are applied with various tracking structures in order to remove or diminish the side peaks, while keeping a sharp and narrow main lobe, thus allowing a better tracking. Five sidelobe cancellation methods (SCM) are proposed and studied: SCM with interference cancellation (IC), SCM with narrow correlator, SCM with high-resolution correlator (HRC), SCM with differential correlation (DC), and SCM with threshold. Compared to other delay tracking methods, the proposed SCM approaches have the advantage that they can be applied to any sine or cosine BOC-modulated signal. We analyze the performances of various tracking techniques in the presence of fading multipath channels and we compare them with other methods existing in the literature. The SCM approaches bring improvement also in scenarios with closely-spaced paths, which are the most problematic from the accurate positioning point of view.</p

Development and Analysis of Advanced Techniques for GNSS Receivers

With the rapid development of digital techniques, the concept of software-defined radio (SDR) emerged which accelerates the first appearance of of the real-time GNSS software receiver at the beginning of this century, in the frame of a software receiver, this thesis mainly explores the possible improvement in parameters estimate such as frequency estimate, code delay estimate and phase estimate. In the first stage, acquisition process is focused, the theoretical mathematical expression of the cross-ambiguity function (CAF) is exploited to analyze the grid and improve the accuracy of the frequency estimate. Based on the simple equation derived from this mathematical expression of the CAF, a family of novel algorithms are proposed to refine the Doppler frequency estimate. In an ideal scenario where there is no noise and other nuisances, the frequency estimation error can be theoretically reduced to zero. On the other hand, in the presence of noise, the new algorithm almost reaches the Cramer-Rao Lower Bound (CRLB) which is derived as benchmark. For comparison, a least-square (LS) method is proposed. It is shown that the proposed solution achieves the same performance of LS, but requires a dramatically reduced computational burden. An averaging method is proposed to mitigate the influence of noise, especially when signal-to-noise ratio (SNR) is low. Finally, the influence of the grid resolution in the search space is analyzed in both time and frequency domains. In the next step, a new FLL discriminator based on energy is proposed to adapt to the changes brought by the new introduced signal modulation. This new discriminator can determine the frequency error only using the minimum period of data, it can also extend the pull-in range to nearly six times larger as the traditional arctangent discriminator. The whole derivation of the method is presented. From the comparison with traditional ATAN and another similar discriminator that is also based on energy, it is shown that the new proposed discriminator can inherit the merits of these two references, avoiding their drawbacks at the same time. Owing to the property of the new discriminator, in case of composite GNSS signals such as Galileo E1 Open Service (OS) signal, coherent combination of data and pilot channels can be adopted to improve the frequency estimate by exploiting the full transmitted power. In order to incorporate all the available information, the structure of a tracking loop with Extended Kalman Filter (EKF) is analyzed and implemented. The structure of an EKF-based software receiver is proposed including the special modules dedicated to the initialization and maintenance of the tracking loop. The EKF-based tracking architecture has been compared with a traditional one based on an FLL/PLL+DLL architecture, and the benefit of the EKF within the tracking stage has been evaluated in terms of final positioning accuracy. Further tests have been carried out to compare the Position-Velocity-Time (PVT) solution of this receiver with the one provided by two commercial receivers: a mass-market GPS module (Ublox LEA-5T) and a professional one (Septentrio PolaRx2e@). The results show that the accuracy in PVT of the software receiver can be remarkably improved if the tracking is designed with a proper EKF architecture and the performance we can achieve is even better than the one obtained by the mass market receiver, even when a simple one-shot least-squares approach is adopted for the computation of the navigation solution. Furthermore in depth, KF-based tracking loop is analyzed, a control model is derived to link the KF system and the traditional one which can provide an insight into the advantages of KF system. Finally, conclusions and main recommendations are presented

Adaptive Interference Mitigation in GPS Receivers

Satellite navigation systems (GNSS) are among the most complex radio-navigation systems, providing positioning, navigation, and timing (PNT) information. A growing number of public sector and commercial applications rely on the GNSS PNT service to support business growth, technical development, and the day-to-day operation of technology and socioeconomic systems. As GNSS signals have inherent limitations, they are highly vulnerable to intentional and unintentional interference. GNSS signals have spectral power densities far below ambient thermal noise. Consequently, GNSS receivers must meet high standards of reliability and integrity to be used within a broad spectrum of applications. GNSS receivers must employ effective interference mitigation techniques to ensure robust, accurate, and reliable PNT service. This research aims to evaluate the effectiveness of the Adaptive Notch Filter (ANF), a precorrelation mitigation technique that can be used to excise Continuous Wave Interference (CWI), hop-frequency and chirp-type interferences from GPS L1 signals. To mitigate unwanted interference, state-of-the-art ANFs typically adjust a single parameter, the notch centre frequency, and zeros are constrained extremely close to unity. Because of this, the notch centre frequency converges slowly to the target frequency. During this slow converge period, interference leaks into the acquisition block, thus sabotaging the operation of the acquisition block. Furthermore, if the CWI continuously hops within the GPS L1 in-band region, the subsequent interference frequency is locked onto after a delay, which means constant interference occurs in the receiver throughout the delay period. This research contributes to the field of interference mitigation at GNSS's receiver end using adaptive signal processing, predominately for GPS. This research can be divided into three stages. I first designed, modelled and developed a Simulink-based GPS L1 signal simulator, providing a homogenous test signal for existing and proposed interference mitigation algorithms. Simulink-based GPS L1 signal simulator provided great flexibility to change various parameters to generate GPS L1 signal under different conditions, e.g. Doppler Shift, code phase delay and amount of propagation degradation. Furthermore, I modelled three acquisition schemes for GPS signals and tested GPS L1 signals acquisition via coherent and non-coherent integration methods. As a next step, I modelled different types of interference signals precisely and implemented and evaluated existing adaptive notch filters in MATLAB in terms of Carrier to Noise Density (\u1d436/\u1d4410), Signal to Noise Ratio (SNR), Peak Degradation Metric, and Mean Square Error (MSE) at the output of the acquisition module in order to create benchmarks. Finally, I designed, developed and implemented a novel algorithm that simultaneously adapts both coefficients in lattice-based ANF. Mathematically, I derived the full-gradient term for the notch's bandwidth parameter adaptation and developed a framework for simultaneously adapting both coefficients of a lattice-based adaptive notch filter. I evaluated the performance of existing and proposed interference mitigation techniques under different types of interference signals. Moreover, I critically analysed different internal signals within the ANF structure in order to develop a new threshold parameter that resets the notch bandwidth at the start of each subsequent interference frequency. As a result, I further reduce the complexity of the structural implementation of lattice-based ANF, allowing for efficient hardware realisation and lower computational costs. It is concluded from extensive simulation results that the proposed fully adaptive lattice-based provides better interference mitigation performance and superior convergence properties to target frequency compared to traditional ANF algorithms. It is demonstrated that by employing the proposed algorithm, a receiver is able to operate with a higher dynamic range of JNR than is possible with existing methods. This research also presents the design and MATLAB implementation of a parameterisable Complex Adaptive Notch Filer (CANF). Present analysis on higher order CANF for detecting and mitigating various types of interference for complex baseband GPS L1 signals. In the end, further research was conducted to suppress interference in the GPS L1 signal by exploiting autocorrelation properties and discarding some portion of the main lobe of the GPS L1 signal. It is shown that by removing 30% spectrum of the main lobe, either from left, right, or centre, the GPS L1 signal is still acquirable

The Global Navigation System Scope (GNSScope): a toolbox for the end-to-end modelling simulation and analysis of GNSS

The thesis provides a detailed overview of the work carried out by the author over the course of the research for the award of the degree of Doctor of Philosophy at the University of Westminster, and the performance results of the novel techniques introduced into the literature. The outcome of the work is collectively referred to as the Global Navigation System Scope (GNSScope) Toolbox, offering a complete, fully reconfigurable platform for the end-to-end modeling, simulation and analysis of satellite navigation signals and systems, covering the signal acquisition, tracking, and range processing operations that take place in a generic Global Navigation Satellite System (GNSS) receiver, accompanied by a Graphical User Interface (GUI) providing access to all the techniques available in the toolbox. Designed and implemented entirely in the MATLAB mathematical programming environment using Software Defined Radio (SDR) receiver techniques, the toolbox offers a novel new acquisition algorithm capable of handling all Phase-Shift Keying (PSK) type modulations used on all frequency bands in currently available satellite navigation signals, including all sub-classes of the Binary Offset Carrier (BOC) modulated signals. In order to be able to process all these signals identified by the acquisition search, a novel tracking algorithm was also designed and implemented into the toolbox to track and decode all acquired satellite signals, including those currently intended to be used in future navigation systems, such as the Galileo test signals transmitted by the GIOVE satellites orbiting the Earth. In addition to the developed receiver toolbox, three novel algorithms were also designed to handle weak signals, multipath, and multiple access interference in GNSScope. The Mirrored Channel Mitigation Technique, based on the successive and parallel interference cancellation techniques, reduces the hardware complexity of the interference mitigation process by utilizing the local code and carrier replicas generated in the tracking channels, resulting in a reduction in hardware resources proportional to the number of received strong signals. The Trigonometric Interference Cancellation Technique, used in cross-correlation interference mitigation, exploits the underlying mathematical expressions to simplify the interference removal process, resulting in reduced complexity and execution times by reducing the number of operations by 25% per tracking channel. The Split Chip Summation Technique, based on the binary valued signal modulation compression technique, enhances the amount of information captured from compressing the signal to reveal specific filtering effects on the positive and negative polarity chips of the spreading code. Simulation case studies generated entirely using the GNSScope toolbox will be used throughout the thesis to demonstrate the effectiveness of the novel techniques developed over the course of the research, and the results will be compared to those obtained from other techniques reported in the literature

Analyzing Code Tracking Algorithms for Galileo Open Service Signal

The ever-increasing public interest on location and positioning services has originated a demand for higher performance Global Navigation Satellite Systems (GNSSs). Galileo Open Service (OS) signal, part of the European contribution to future GNSS, was designed to respond to the above demand. In all GNSSs, the estimation with high accuracy of the Line-Of-Sight (LOS) delay is a prerequisite. The Delay Lock Loops (DLLs) and their enhanced variants (i.e., feed-back code tracking loops) are the structures of choice for the commercial GNSS receivers, but their performance in severe multipath scenarios is still rather limited. In addition, the new satellite positioning system proposals specify the use of a new modulation, the Binary Offset Carrier (BOC) modulation, which triggers a new challenge in the code tracking stage. Therefore, in order to meet this emerging challenge and to improve the accuracy of the delay estimation in severe multipath scenarios, this thesis analyzes feed-back as well as feed-forward code tracking algorithms and proposes a novel algorithm, namely Peak Tracking (PT), which is a combination of both feed-back and feed-forward structures and utilizes the advantages inherent in these structures. In this thesis, the code tracking algorithms are studied and analyzed for Sine BOC (SinBOC) modulated Galileo OS signal for various multipath profiles in Rayleigh fading channel model. The performance of the analyzed algorithms are measured in terms of various well-known criteria such as Root-Mean-Square-Error (RMSE), Mean-Time-to-Lose Lock (MTLL), delay error variance and Multipath Error Envelopes (MEEs). The simulation results show that the proposed PT algorithm outperforms all other analyzed algorithms in various multipath profiles in good Carrier-to-Noise-Ratios (CNRs). The simulation results are compared with the theoretical Cramer-Rao Bound (CRB) and the comparison shows that the delay error variance for PT algorithm approaches the theoretical limit with the increase in CNR. Therefore, the proposed algorithm can be considered as an excellent candidate for implementation in future Galileo receivers, especially when tracking accuracy is a concern. /Kir1

Performance of precise marine positioning using future modernised global satellite positioning systems and a novel partial ambiguity resolution technique

The International Maritime Organisation (IMO) established a set of positioning requirements for future Global Navigation Satellite System (GNSS) constellations in IMO resolution A.915. It is important to be able to determine if these requirements can be met, and what shore infrastructure would be required. This thesis describes the collection of data in a marine environment and the analysis of these data with regards to the requirements. The data collection exercise was held at the beginning of May 2008 and saw THV Alert navigate into Harwich Harbour whilst Global Positioning System (GPS) observation data were recorded from onboard the vessel and from shore-based reference stations. Additional data were obtained from nearby Ordnance Survey reference stations, and two total stations were used to track the vessel’s passage to provide a truth model. Several modernised GPS satellites were tracked. The data were processed under different scenarios, using software developed at UCL, and the positioning performance was analysed in the context of the IMO requirements. Potential performance improvements from modernised GPS and Galileo were then discussed. Providing integrity through single-epoch real-time kinematic positioning, required to meet the strictest IMO requirements, is particularly difficult. The identification of phase observation outliers is not possible before the integer ambiguities are resolved, but an undetected outlier could prevent successful ambiguity resolution. It will not always be necessary to fix all the ambiguities to achieve the required positioning precision, particularly with a multi-GNSS constellation. This thesis introduces a new algorithm for partial ambiguity resolution in the presence of measurement bias. Although computationally intensive, this algorithm significantly improves the ambiguity resolution success rate, increasing the maximum baseline length over which the highest requirements are met with dual-frequency GPS from 1 km to 66 km

Signal processing techniques for GNSS anti-spoofing algorithms

The Global Navigation Satellite Systems (GNSS) usage is growing at a very high rate, and more applications are relying on GNSS for correct functioning. With the introduction of new GNSSs, like the European Galileo and the Chinese Beidou, in addition to the existing ones, the United States Global Positioning System (GPS) and the Russian GLONASS, the applications, accuracy of the position and usage of the signals are increasing by the day. Given that GNSS signals are received with very low power, they are prone to interference events that may reduce the usage or decrease the accuracy. From these interference, the spoofing attack is the one that has drawn major concerns in the GNSS community. A spoofing attack consist on the transmission of GNSS-like signals, with the goal of taking control of the receiver and make it compute an erroneous position and time solution. In the thesis, we focus on the design and validation of different signal processing techniques, that aim at detection and mitigation of the spoofing attack effects. These are standalone techniques, working at the receiver’s level and providing discrimination of spoofing events without the need of external hardware or communication links. Four different techniques are explored, each of them with its unique sets of advantages and disadvantages, and a unique approach to spoofing detection. For these techniques, a spoofing detection algorithm is designed and implemented, and its capabilities are validated by means of a set of datasets containing spoofing signals. The thesis focuses on two different aspects of the techniques, divided as per detection and mitigation capabilities. Both detection techniques are complementary, their joint use is explored and experimental results are shown that demonstrate the advantages. In addition, each mitigation technique is analyzed separately as they require specialized receiver architecture in order to achieve spoofing detection and mitigation. These techniques are able to decrease the effects of the spoofing attacks, to the point of removing the spoofing signal from the receiver and compute navigation solutions that are not controlled by the spoofer and lead in more accurate end results. The main contributions of this thesis are: the description of a multidimensional ratio metric test for distinction between spoofing and multipath effects; the introduction of a cross-check between automatic gain control measurements and the carrier to noise density ratio, for distinction between spoofing attacks and other interference events; the description of a novel signal processing method for detection and mitigation of spoofing effects, based on the use of linear regression algorithms; and the description of a spoofing detection algorithm based on a feedback tracking architecture

Physical Layer Challenges and Solutions in Seamless Positioning via GNSS, Cellular and WLAN Systems

As different positioning applications have started to be a common part of our lives, positioning methods have to cope with increasing demands. Global Navigation Satellite System (GNSS) can offer accurate location estimate outdoors, but achieving seamless large-scale indoor localization remains still a challenging topic. The requirements for simple and cost-effective indoor positioning system have led to the utilization of wireless systems already available, such as cellular networks and Wireless Local Area Network (WLAN). One common approach with the advantage of a large-scale standard-independent implementation is based on the Received Signal Strength (RSS) measurements.This thesis addresses both GNSS and non-GNSS positioning algorithms and aims to offer a compact overview of the wireless localization issues, concentrating on some of the major challenges and solutions in GNSS and RSS-based positioning. The GNSS-related challenges addressed here refer to the channel modelling part for indoor GNSS and to the acquisition part in High Sensitivity (HS)-GNSS. The RSSrelated challenges addressed here refer to the data collection and calibration, channel effects such as path loss and shadowing, and three-dimensional indoor positioning estimation.This thesis presents a measurement-based analysis of indoor channel models for GNSS signals and of path loss and shadowing models for WLAN and cellular signals. Novel low-complexity acquisition algorithms are developed for HS-GNSS. In addition, a solution to transmitter topology evaluation and database reduction solutions for large-scale mobile-centric RSS-based positioning are proposed. This thesis also studies the effect of RSS offsets in the calibration phase and various floor estimators, and offers an extensive comparison of different RSS-based positioning algorithms

Analysis and Detection of Outliers in GNSS Measurements by Means of Machine Learning Algorithms

L'abstract è presente nell'allegato / the abstract is in the attachmen