A Novel Carrier Loop Based on Adaptive LM-QN Method in GNSS Receivers

A well-designed carrier tracking loop in a receiver of the Global Navigation Satellite System (GNSS) is the premise of accurate positioning and navigation in an aircraft-based surveying and mapping system. To deal with the problems of Doppler estimation in high-dynamic maneuvers, the interest on maximum-likelihood estimation (MLE) is increasing among the academic community. Levenberg-Marquardt (LM) method is usually regarded as an effective and promising approach to obtain the solution of MLE, but the computation of Hessian matrix loads a great burden on the algorithm. Besides, a poor performance on convergency in final iterations is the common failing of LM implementations. To solve these problems, an LM method based on Gauss-Newton and a Quasi-Newton (QN) method based on Hessian approximation are derived, making the computation cost of Hessian decline from O(N) to O(1). Then, on the basis of these two methods, a closed carrier loop with adaptive LM-QN algorithm is further proposed which can switch between LM and QN adaptively according to a damping parameter. Besides, an ideal LM with super-linear convergence (SLM) is constructed and proved as a reference of the convergence analysis. Finally, through the analyses and experiments using aircraft data, the improvements on computation cost and convergence are verified. Compared with scalar tracking and vector tracking, results indicate a magnitude increase in the precision of LM-QN loop, even though more computation counts are needed by LM-QN.Peer reviewe

Doppler Frequency Estimation in GNSS Receivers Based on Double FFT

This work presents an innovative Doppler frequency estimation technique, particularly suited for GNSS receivers operating in vehicular scenarios. Mass-market and commercial navigation devices are more and more exploited for in-car navigation and for vehicular applications based on positioning. However, the low computational burden affordable by such devices requires the implementation of low complexity algorithms, allowing real-time and on-demand processing. This is the case for instance of open-loop architectures and of MLE-based techniques, which estimate the frequency component of the GNSS signal through a discrete Fourier transform. A state-of-the-art of such methods is first carried out, outlining their benefits, regarding robustness and stability, and their limitations, mainly concerning the accuracy. Successively an innovative refinement technique is introduced, based on the computation of a frequency correction term. Further enhancements are then proposed to solve particular issues, as the estimation of the sign of the correction term and the impact of the initial frequency error. In particular, zero-forcing and a double FFT – which represent the main contribution of this work – are proposed to increase the accuracy without increasing the computational load. A complete analytical derivation and theoretical description is provided, along with a detailed performance assessment. Finally a performance comparison with existing techniques and with the Cramer-Rao lower bound for frequency estimation is given, confirming the excellent behavior of the proposed algorithm for the signal conditions and strengths typical of a vehicular scenario and in the presence of frequent interruptions

Doppler Frequency Estimation in GNSS Receivers Based on Double FFT

This work presents an innovative Doppler frequency estimation technique, particularly suited for GNSS receivers operating in vehicular scenarios. Mass-market and commercial navigation devices are more and more exploited for in-car navigation and for vehicular applications based on positioning. However, the low computational burden affordable by such devices requires the implementation of low complexity algorithms, allowing real-time and on-demand processing. This is the case for instance of open-loop architectures and of MLE-based techniques, which estimate the frequency component of the GNSS signal through a discrete Fourier transform. A state-of-the-art of such methods is first carried out, outlining their benefits, regarding robustness and stability, and their limitations, mainly concerning the accuracy. Successively an innovative refinement technique is introduced, based on the computation of a frequency correction term. Further enhancements are then proposed to solve particular issues, as the estimation of the sign of the correction term and the impact of the initial frequency error. In particular, zero-forcing and a double FFT – which represent the main contribution of this work – are proposed to increase the accuracy without increasing the computational load. A complete analytical derivation and theoretical description is provided, along with a detailed performance assessment. Finally a performance comparison with existing techniques and with the Cramer-Rao lower bound for frequency estimation is given, confirming the excellent behavior of the proposed algorithm for the signal conditions and strengths typical of a vehicular scenario and in the presence of frequent interruptions

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

New methods and architectures for high sensitivity hybrid GNSS receivers in challenging environments

GNSS satellite navigation systems are constantly evolving and have been already used in many applications. With the advent of the new systems Galileo and BeiDou as well as the modernization of GPS and GLONASS systems, new satellites and numerous new frequencies and signals will appear in the coming years and will open door to countless new applications that are currently impossible. The rapid evolution of mobile telephony and personal navigation devices (PND) requires better use of navigation systems in non-ideal environments, especially the need for positioning in deep urban area. On the one hand, users are waiting for a high positioning accuracy, because of the proximity to various points of interest. On the other hand, urban environment brings specific difficulties in receiving GNSS signals. GNSS navigation signals cannot be properly captured in urban and "indoor" environments. Signal levels are very low and it is almost impossible to acquire and track signals autonomously because of the strong attenuation of signals due to obstacles. In addition, indoor and urban positioning are also subject to multipath problems, masking, interference and jamming. Under these conditions, we must be able to process highly degraded or very short signals that do not allow the receiver to go through the tracking process. Thus, this leads us to the need to rethink the architecture of GNSS receiver for modern applications. This thesis project consists of developing new GNSS methods and architectures of high sensitivity and robustness to signal degradations and designing new algorithms integrated into a hybrid GNSS receiver capable of operating in deep urban environments. The methodology involves the use of the new concept of “Collective Detection (CD)”, also called “collaborative acquisition”. The collaborative approach that treats multi-satellite signals all together opens an interesting solution. Many techniques exist in the literature to solve the problems of positioning in urban environments, but we propose the new Collective Detection approach because of its performance as both a Direct Positioning (DP) method, providing a coarse position/clock-bias solution directly from acquisition, and High-Sensitivity (HS) acquisition method, by application of vector detection of all satellites in view. Indeed, the correct combination of the correlation values of several satellites can reduce the required Carrier-to-Noise Ratio (C/No) level of the satellite signals which cannot be acquired individually by standard signal processing (acquisition and tracking) but make it possible to use them constructively to a positioning solution. The combination of different GNSS signals can considerably increase the acquisition sensitivity of the receiver. Despite the advantages of this approach, it also has drawbacks such as the high computational burden because of the large number of candidate points in the position/clock-bias domain. Thus, the work proposed in this thesis consists of reducing the complexity of the CD by optimizing the search for candidate points in position/clock-bias domain. Finally, the goal is to apply the CD approach to Cooperative GNSS Positioning for modern navigation in harsh environments. For that, algorithms for optimally exploiting receiver resources by selecting the best satellites or the reference station will be developed according to certain criteria such as the C/No level, the elevation angle, and the geometric configuration of the visible satellites. The ultimate goal is to propose a design of a new smart receiver “High Sensitivity Cognitive GNSS Receiver (HSCGR)” to optimally receive and process GNSS signals