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