卫星导航系统中基于序贯处理的Kalman滤波

为了有效降低基于Kalman滤波方法的导航定位求解运算量,保证实时性,提出了一种以单个卫星为基本滤波单元的基于序贯处理的扩展Kalman滤波(EKF,extended Kalman filtering)方法——单星序贯扩展Kalman滤波(S3EKF,single-satellite sequential extended Kalman filtering)法。仿真结果表明,S3EKF法相对常规EKF法而言,当可见卫星数超过7颗时,能有效改善运算量,且改善量随可见卫星数的增加而增加,当可见卫星数在15颗及以上时,运算量的改善超过50%;同时,S3EKF法能在可见卫星发生变化时保证求解的一致性和稳定性。

Application of Kalman filtering based on sequential processing for satellite navigation

In order to reduce the operational volume and ensure the real-time capability of navigation algorithm of Kal-man filtering,a novel filtering method called single-satellite sequential extended Kalman filtering(S3EKF) was proposed based on extended Kalman filtering(EKF) and sequential processing,where the single-satellite was as basic filtering unit.Simulation results show that,compared with the traditional EKF method,the S3EKF method can decrease the computa-tion load efficiently when the number of visible satellites is no less than 7,and the reduction of computation load in-creases with the increase of the satellite’s visible number,the decrease will reach more than 50% when the number of visible satellites is no less than 15.On the other hand,the consistency and stability of navigation solution are good when the satellites and their number are time-vraiant in S3EKF method.