Research On The Performance Of Carrier Tracking In High Dynamic Gnss Receiver

Currently, the Global Navigation Satellite System (GNSS) has penetrated into many fields all over the world, becoming a positioning information infrastructure which providing all-weather navigation space service. As GNSS has broad application prospects and huge industrial benefits, space powers are struggling to develop and popularize their own satellite navigation receivers. However, due to the Doppler frequency shift of the satellite signal and its very large change rate in the aviation, aerospace, missile guidance and other application areas, traditional carrier tracking loop is difficult to bear the dynamic stress caused by high-speed motion and easily loses lock, so the receiver can’t work. This paper intends to solve the problem of performance optimization and robustness design in carrier tracking loop under high dynamic environment, which can provide the theoretical basis for the development of high dynamic GNSS navigation receiver.The constitution of GNSS and principle component of receiver are firstly introduced in this paper, and baseband intermediate frequency signal source is generated according to the high dynamic GNSS signal model. The dynamic limitation of traditional tracking loop and tracking loop based on the theory of signal parameter estimation are mainly illustrated in the paper. Then, in order to break through the limitations of traditional loop tracking performance and propose several robustness high dynamic carrier tracking loop, Kalman filter theory and particle filter theory are introduced to design tracking loop based on the high dynamic motion model of the receiver. The main work of this paper can be summarized as follows:(1) Considering that traditional loop bandwidth must be a compromise between dynamic stress and tracking accuracy, the optimal bandwidth optimization algorithm is studied and a strong tracking and adaptive filtering (ASTF) carrier tracking loop algorithm is proposed in the paper. We design two kinds of loop structure for the algorithm implementation:closed loop structure with a discriminator and parameter estimation structure. The loop performance of ASTF is theoretically analyzed to derive the structural equivalence between closed-loop structure and phase locked loop, and proof the steady-state bandwidth adjustment capability. Besides, the performance difference between the closed-loop structure and parameter estimation structure is discussed.(2) For avoiding low tracking precision and reducing computational complexity which caused by calculating Jacoby matrix of the nonlinear observer model in strong tracking adaptive filter, an adaptive square root unscented Kalman filter (ASRUKF) carrier tracking loop is designed in a parameter estimation structure with adaptive fading factor based on the new covariance. Since the approximation accuracy of UT transform can reach more than the second order, the tracking accuracy of ASRUKF is higher than ASTF.(3) Based on Bayesian estimation theory and particle filter algorithm, a Gaussian particle filter (GPF) carrier tracking loop and the corresponding loop implementation are proposed in this paper. In order to eliminate the sensitivity to initial value and unreasonable proposal distribution, two optimization methods are proposed in the original algorithm framework, including strong tracking filter optimization (STF-GPF) and unscented Kalman filter optimization (UGPF), which greatly enhance the robustness and tracking accuracy of GPF. The loop takes advantage of the superior performance of particle filter, and improves effectively tracking accuracy and sensitivity of the receiver.The proposed algorithms are tested to verify the feasibility under high dynamic simulation in the software receiver platform, and have a good tracking performance. The research has certain significance for the performance optimization of high dynamic GNSS receiver.