卫星导航系统中基于序贯处理的Kalman滤波  

Application of Kalman filtering based on sequential processing for satellite navigation

作　　者：陈灿辉[1] 张晓林[1] 霍航宇[1] 

机构地区：[1]北京航空航天大学电子信息工程学院,北京100191

出　　处：《通信学报》2012年第1期174-181,共8页Journal on Communications

基　　金：国防科工局航天民用专项;北京市重点学科基金资助项目(XK100070525)~~

摘　　要：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。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.

关 键 词：卫星导航 扩展Kalman滤波 序贯处理 最小二乘法 运算量 

分 类 号：TN967.1[电子电信—信号与信息处理]