Unambiguous Acquisition and Tracking Technique for General BOC Signals

This article presents a new unambiguous acquisition and tracking technique for general Binary Offset Carrier (BOC) ranging signals, which will be used in modern GPS, European Galileo system and Chinese BeiDou system. The test criterion employed in this technique is based on a synthesized correlation function which completely removes positive side peaks while keeping the sharp main peak. Simulation results indicate that the proposed technique completely removes the ambiguity threat in the acquisition process while maintaining relatively higher acquisition performance for low order BOC signals. The potential false lock points in the tracking phase for any order BOC signals are avoided by using the proposed method. Impacts of thermal noise and multipath on the proposed technique are investigated; the simulation results show that the new method allows the removal of false lock points with slightly degraded tracking performance. In addition, this method is convenient to implement via logic circuits

Unambiguous Tracking Method Based on Combined Correlation Functions for sine/cosine-BOC CBOC and AltBOC Modulated Signals

Unambiguous tracking for Binary Offset Carrier (BOC) modulated signals is an important requirement of modern Global Navigation Satellite System (GNSS) receivers. An unambiguous tracking method based on combined correlation functions for even/odd order sine/cosine-BOC, Composite BOC(CBOC) and Alternate BOC(AltBOC) modulated signals is proposed. Firstly, a unitary mathematical formulation for all kinds of BOC modulations is introduced. Then an unambiguous tracking method is proposed based on the formulation and the idea of pseudo correlation function (PCF) method. Finally, the tracking loop based on the proposed method is designed. Simulation results indicate that the proposed method can remove side peaks while retaining the sharp main peak for all kinds of BOC modulations. The tracking performance for AltBOC is examined and the results show that the proposed method has better performance in thermal noise and long-delay multipath mitigation than the traditional unambiguous tracking methods

Collective unambiguous positioning with high-order BOC signals

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The unambiguous estimation of high-order BOC signals in harsh propagation conditions is still an open problem in the literature. This paper proposes to overcome the limitations observed in state-of-the-art unambiguous estimation techniques based on the application of existing direct positioning techniques and the exploitation of the spatial diversity introduced by arrays of antennas. In particular, the ambiguity problem is solved as a multiple-input multiple-output (MIMO) estimation problem in the position domain.Peer ReviewedPostprint (author's final draft

GNSS signal acquisition in the presence of sign transitions

The next generation of Global Navigation Satellite Systems (GNSS), such as Galileo [1] and GPS modernization [2], will use signals with equal code and bit periods, which will introduce a potential sign transition in each segment of the signal processed in the acquisition block. If FFT is used to perform the correlations a sign transition occurring within the integration time may cause a splitting of the main peak of the Cross Ambiguity Function (CAF) into two smaller lobes along the Doppler shift axis [3]. In this paper a method to overcome the possible impairments due to the lobe splitting is proposed and validated by simulatio

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

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

Design and Validation of a Software Receiver for Galileo

This paper presents a new concept of software-based GNSS receivers for the Binary Offset Carrier signals of the Galileo testbed satellites, Giove-A and Giove-B. The receiver designed in Matlab must be able to acquire, track and demodulate both signals. Its advantages in terms of flexibility and reconfigurability make it an excellent instrument to test new designs or new prototypes as a previous stage on a hardware implementation

Multi-GNSS signals acquisition techniques for software defines receivers

Any commercially viable wireless solution onboard Smartphones should resolve the technical issues as well as preserving the limited resources available such as processing and battery. Therefore, integrating/combining the process of more than one function will free up much needed resources that can be then reused to enhance these functions further. This thesis details my innovative solutions that integrate multi-GNSS signals of specific civilian transmission from GPS, Galileo and GLONASS systems, and process them in a single RF front-end channel (detection and acquisition), ideal for GNSS software receiver onboard Smartphones. During the course of my PhD study, the focus of my work was on improving the reception and processing of localisation techniques based on signals from multi-satellite systems. I have published seven papers on new acquisition solutions for single and multi-GNSS signals based on the bandpass sampling and the compressive sensing techniques. These solutions, when applied onboard Smartphones, shall not only enhance the performance of the GNSS localisation solution but also reduce the implementation complexity (size and processing requirements) and thus save valuable processing time and battery energy. Firstly, my research has exploited the bandpass sampling technique, if being a good candidate for processing multi-signals at the same time. This portion of the work has produced three methods. The first method is designed to detect the GPS, Galileo and GLONASS-CDMA signals’ presence at an early stage before the acquisition process. This is to avoid wasting processing resources that are normally spent on chasing signals not present/non-existent. The second focuses on overcoming the ambiguity when acquiring Galileo-OS signal at a code phase resolution equal to 0.5 Chip or higher and this achieved by multiplying the received signal with the generated sub-carrier frequency. This new conversion saves doing a complete correlation chain processing when compared to conventionally used methods. The third method simplifies the joining implementation of the Galileo-OS data-pilot signal acquisition by constructing an orthogonal signal so as to acquire them in a single correlation chain, yet offering the same performance as using two correlation chains. Secondly, the compressive sensing technique is used to acquire multi-GNSS signals to achieve computation complexity reduction over correlator based methods, like Matched Filter, while still maintaining acquisition integrity. As a result of this research work, four implementation methods were produced to handle single or multi-GNSS signals. The first of these methods is designed to change dynamically the number and the size of the required channels/correlators according to the received GPS signal-power during the acquisition process. This adaptive solution offers better fix capability when the GPS receiver is located in a harsh signal environment, or it will save valuable processing/decoding time when the receiver is outdoors. The second method enhances the sensing process of the compressive sensing framework by using a deterministic orthogonal waveform such as the Hadamard matrix, which enabled us to sample the signal at the information band and reconstruct it without information loss. This experience in compressive sensing led the research to manage more reduction in terms of computational complexity and memory requirements in the third method that decomposes the dictionary matrix (representing a bank of correlators), saving more than 80% in signal acquisition process without loss of the integration between the code and frequency, irrespective of the signal strength. The decomposition is realised by removing the generated Doppler shifts from the dictionary matrix, while keeping the carrier frequency fixed for all these generated shifted satellites codes. This novelty of the decomposed dictionary implementation enabled other GNSS signals to be combined with the GPS signal without large overhead if the two, or more, signals are folded or down-converted to the same intermediate frequency. The fourth method is, therefore, implemented for the first time, a novel compressive sensing software receiver that acquires both GPS and Galileo signals simultaneously. The performance of this method is as good as that of a Matched Filter implementation performance. However, this implementation achieves a saving of 50% in processing time and produces a fine frequency for the Doppler shift at resolution within 10Hz. Our experimental results, based on actual RF captured signals and other simulation environments, have proven that all above seven implementation methods produced by this thesis retain much valuable battery energy and processing resources onboard Smartphones