高動態(tài)GNSS接收機(jī)載波跟蹤的性能研究
[Abstract]:At present, Global Satellite Navigation system (GNSS) has penetrated into many fields all over the world and become a kind of spatial information infrastructure to provide all-weather navigation and positioning service. All the big spaceflight countries are making great efforts to develop and promote their navigation receivers. However, in the fields of aerospace, aerospace and missile guidance, the Doppler frequency shift and its rate of change of satellite signals are very large, and the traditional carrier tracking loop is difficult to withstand the dynamic stress caused by high-speed motion, so it is easy to lose lock. The receiver does not work. In this paper, the performance optimization and robustness design of carrier tracking loop in high dynamic environment are solved, which provides a theoretical basis for the development of high dynamic GNSS navigation receiver in China. In this paper, the structure of GNSS system and the principle of receiver are introduced firstly. Secondly, the high dynamic GNSS signal model is constructed and the baseband intermediate frequency signal source is generated. Then the limitation of the traditional tracking loop to the dynamic stress and the tracking loop based on the theory of signal parameter estimation are expounded. Finally, aiming at the high dynamic motion model of the receiver, Kalman filter theory and particle filter theory are introduced into the loop structure design to break through the limitations of the traditional tracking loop performance. Several carrier tracking loops suitable for high dynamic environment are proposed. The main work of this paper can be summarized as follows: (1) in order to solve the contradiction between dynamic stress and tracking accuracy in traditional loop, the optimal bandwidth optimization algorithm is studied. A high dynamic carrier tracking loop based on strong tracking adaptive filter (ASTF) is proposed and two implementation structures are designed: closed loop structure with discriminator and parameter estimation structure. By analyzing the performance of the ASTF loop, the equivalence of the closed loop structure and the phase locked loop structure is deduced, and the steady-state bandwidth adjustment capability brought by the strong tracking mechanism is proved. Finally, the performance difference between the parameter estimation structure and the closed loop structure is discussed. (2) in order to solve the problem of reduced tracking accuracy and high algorithm complexity caused by Jacobi matrix when ASTF loop is used to deal with nonlinear observation model, an adaptive fading factor based on innovation covariance is introduced into square root unscented Kalman filter. A high dynamic carrier tracking loop based on adaptive square root unscented Kalman filter (ASRUKF) is proposed and its parameter estimation architecture is designed. Because the approximation accuracy of UT transform is higher than the second order, the tracking accuracy of ASRUKF loop is higher than that of ASTF. (3) based on Bayesian optimal estimation and particle filter theory, a high dynamic carrier tracking loop based on Gao Si particle filter (GPF) is proposed. The corresponding loop implementation scheme is designed and its performance is analyzed. In order to solve the problem of sensitivity of GPF to initial values and unreasonable distribution of recommendations, two optimization methods, strong tracking filter (STF-GPF) and unscented Kalman filter (UGPF), are proposed in the framework of the original algorithm. The GPF loop makes use of the superior performance of particle filter to improve the sensitivity and tracking performance of the receiver effectively. The algorithm proposed in this paper is tested on the software receiver platform by high dynamic simulation, and the feasibility of the algorithm is verified, and good tracking performance is obtained. It can be used for reference to study the performance optimization algorithm of high dynamic GNSS receiver in our country.
【學(xué)位授予單位】:廈門大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:TN965.5
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