基于UKF的北斗/INS组合导航  

GNSS /INS Integrated Navigation Based on UKF

作　　者：王维锋[1] 徐万里[1] 聂挥宇[1] 

机构地区：[1]装甲兵工程学院信息工程系,北京100072

出　　处：《四川兵工学报》2013年第8期96-99,共4页Journal of Sichuan Ordnance

基　　金：国家自然科学基金资助(41271402)

摘　　要：扩展卡尔曼滤波(EKF)是工程中常用的滤波算法,然而EKF是次优的贝叶斯估计,这会影响到估计的精度;用不敏卡尔曼滤波算法(UKF)取代EKF构建了北斗/INS组合导航系统,实验结果表明:UKF相对于EKF,各项参数的误差均有10%以上的减少量。The extended Kalman filter （EKF） has become one of the most widely used algorithms in engi-neering. Unfortunately, the EKF is based on a sub-optimal implementation of the recursive Bayesian estima-tion framework applied to Gaussian random variables. This can seriously affect the accuracy of the system. We apply the Unscented Kalman Filter （UKF） to GNSS/INS integrated navigation and the experimental re-sults show that the UKF has an error reduction of over 10% in every estimator relative to the EKF.

关 键 词：北斗 INS组合导航 EKF UKF 

分 类 号：TN967.2[电子电信—信号与信息处理]