Analysis of Multipath Mitigation Techniques with Land Mobile Satellite Channel Model

Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Mobile Satellite (LMS) channel model [1]-[4], developed at the German Aerospace Center (DLR). The DLR LMS channel model is widely used for simulating the positioning accuracy of mobile satellite navigation receivers in urban outdoor scenarios. The main objective of this paper is to present a comprehensive analysis of some of the most promising techniques with the DLR LMS channel model in varying multipath scenarios. Four multipath mitigation techniques are chosen herein for performance comparison, namely, the narrow Early-Minus-Late (nEML), the High Resolution Correlator, the C/N0-based two stage delay tracking technique, and the Reduced Search Space Maximum Likelihood (RSSML) delay estimator. The first two techniques are the most popular and traditional ones used in nowadays GNSS receivers, whereas the later two techniques are comparatively new and are advanced techniques, recently proposed by the authors. In addition, the implementation of the RSSML is optimized here for a narrow-bandwidth receiver configuration in the sense that it now requires a significantly less number of correlators and memory than its original implementation. The simulation results show that the reduced-complexity RSSML achieves the best multipath mitigation performance in moderate-to-good carrier-to-noise density ratio with the DLR LMS channel model in varying multipath scenarios

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

Carrier phase recovery for array navigation receiver : a fast phase retrieval approach

A fast carrier phase recovery scheme is developed for satellite navigation receiver using an antenna array based on the phase retrieval theory, in which the antenna array provides sufficient measurement information for the phase recovery algorithm. First, the complex satellite signal model after coherent integration is established using the antenna array. Then, considering symbol uncertainty of the navigation data during the coherent integration time, the carrier phase estimation is formulated as a typical phase retrieval problem. At last, using the squared iterative method (SQUAREM), which is capable of superlinear convergence, a fast variant of the Wirtinger Flow (WF) algorithm is derived to solve the phase recovery problem efficiently without compromising the balance between simplicity and stability. As demonstrated by numerical results, the proposed algorithm outperforms the state-of-the-art in terms of the mean squared error (MSE) convergence. Moreover, the adjustment processes of the carrier phase in the proposed method is validated

Motion Planning for Optimal Information Gathering in Opportunistic Navigation Systems

Motion planning for optimal information gathering in an opportunistic navigation (OpNav) environment is considered. An OpNav environment can be thought of as a radio frequency signal landscape within which a receiver locates itself in space and time by extracting information from ambient signals of opportunity (SOPs). The receiver is assumed to draw only pseudorange-type observations from the SOPs, and such observations are fused through an estimator to produce an estimate of the receiver’s own states. Since not all SOP states in the OpNav environment may be known a priori, the receiver must estimate the unknown SOP states of interest simultaneously with its own states. In this work, the following problem is studied. A receiver with no a priori knowledge about its own states is dropped in an unknown, yet observable, OpNav environment. Assuming that the receiver can prescribe its own trajectory, what motion planning strategy should the receiver adopt in order to build a high-fidelity map of the OpNav signal landscape, while simultaneously localizing itself within this map in space and time? To answer this question, first, the minimum conditions under which the OpNav environment is fully observable are established, and the need for receiver maneuvering to achieve full observability is highlighted. Then, motivated by the fact that not all trajectories a receiver may take in the environment are equally beneficial from an information gathering point of view, a strategy for planning the motion of the receiver is proposed. The strategy is formulated in a coupled estimation and optimal control framework of a gradually identified system, where optimality is defined through various information-theoretic measures. Simulation results are presented to illustrate the improvements gained from adopting the proposed strategy over random and pre-defined receiver trajectories.Aerospace Engineering and Engineering Mechanic

Combined Tracking Strategy Based on Unscented Kalman Filter for Global Positioning System L2C CM/CL Signal

In a global positioning system receiver, the tracking algorithm plays a dominant role since the code delay and Doppler frequency shift need to be accurately estimated as well as their variation over time need to be continuously updated. Combine unscented Kalman filter (UKF) with CM/CL signal to improve the signal tracking precision is proposed. It allow weighting assignment between CM code and CL code incoming signal, masked by a mass of noise, and to describe a UKF tracking loop aiming at decreasing numerical errors. UKF here involves state and measuring equations which calculate absolute offsets to adjust initial code and carrier phase then dramatically decrease the tracking error. In particular, the algorithm is implemented in both open space and jammed environment to highlight the advantages of tracking approach, by comparing single code and combined code, UKF and EKF tracking loop. It proves that signal tracking based on UKF, with low energy dissipation as well as high precision, is particularly appealing for a software receiver implementation

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

Advanced Integration of GNSS and External Sensors for Autonomous Mobility Applications

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