Research And Implementation Of PVT Algorithm For Beidou Satellite Navigation Receiver

Recent years,the construction and application of BeiDou Navigation Satellite System(BDS)has developed rapidly.The most important is the development of Beidou satellite navigation receiver of the application of BDS.Beidou satellite navigation receiver is divided into RF module,baseband digital signal processing module and PVT module.The content of this paper is the PVT algorithm of Beidou satellite navigation receiver.Study on the Beidou satellite navigation PVT algorithm and improve the BDS Positioning accuracy,can be very good to promote the application of the BDS,and break the monopoly position of GPS positioning,ensuring the normal operation of national economy and national security.In this paper,the Beidou satellite navigation PVT solution is studied by two algorithms,the main content is divided into the algorithm's research and implementation.The research of the algorithm is mainly based on the existing research and improved,then use C/C++ to achieve the algorithm.In this paper,I have done the following work.1)The application of the least squares algorithm in the Beidou satellite navigation PVT solution is to solve a nonlinear equation of four elements.The least squares solution is an iterative process.But if the convergence threshold value is too small,it may lead to the iterative convergence cannot be forever and always,in view of this situation,this paper proposes a dynamic threshold setting method to avoid the long time iteration does not converge.2)Each solution of the least square algorithm is isolated,and the solution of the two adjacent moments is not related,and the final solution will be jitter and no coherence,but it has good dynamic characteristics.In real life,the object is in the inertial motion system,and the motion of the object is inertial,and there is an inertial relation between the motion of the two adjacent moments.Kalman filtering algorithm is a mathematical recursive algorithm,depending on the last value calculated the value of next moment,that connects a continuous time solution,the results also seem smooth the final solution,no longer seems to bounce back and forth,so out of the final results was in line with the inertia of moving object however,the dynamic performance is poor,not suitable for high dynamic motion model.So this paper proposes an improved fusion algorithm of two kinds of calculation methods,according to different scenarios of switching between least squares and Kalman filter algorithm,the two algorithms are both.3)In the part of implementation of this algorithm,PVT algorithm,based on least squares main dynamic threshold extended Kalman filter algorithm and the hybrid PVT algorithm based on least squares and Kalman filtering algorithm;finally used MFC to design a PC software to calculation results show the graphical display of the text and the form of the curve.