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基于UKF的GPS/DR组合导航非线性状态估计
引用本文:朱虹,关桂霞,田健仲,关永.基于UKF的GPS/DR组合导航非线性状态估计[J].计算机应用与软件,2008,25(12).
作者姓名:朱虹  关桂霞  田健仲  关永
作者单位:首都师范大学信息工程学院,北京,100037
基金项目:北京市自然科学基金项目 , 北京市高校中青年骨干教师基金项目  
摘    要:GPS/DR组合导航系统是一个非线性系统,以往采用的扩展卡尔曼滤波算法EKF使得函数的整体特性被局部特性所代替,加上噪声的存在使系统的性能进一步下降。为了获得更好的状态估计性能,用无迹卡尔曼滤波算法UKF(Unscente dKalman Filter)实现组合导航系统的非线性状态估计,避免了EKF方法的线性化近似过程,提高了算法的收敛速度和载体的定位精度。仿真结果表明:在非线性状态估计中,UKF滤波方法优于EKF滤波方法。

关 键 词:组合导航  EKF滤波  UKF滤波  定位精度

NON-LINEAR STATE ESTIMATION FOR GPS-DR INTEGRATED NAVIGATION BASED ON UKF
Zhu Hong,Guan Guixia,Tian Jianzhong,Guan Yong.NON-LINEAR STATE ESTIMATION FOR GPS-DR INTEGRATED NAVIGATION BASED ON UKF[J].Computer Applications and Software,2008,25(12).
Authors:Zhu Hong  Guan Guixia  Tian Jianzhong  Guan Yong
Affiliation:Zhu Hong Guan Guixia Tian Jianzhong Guan Yong(College of Information Engineering,Capital Normal University,Beijing 100037,China)
Abstract:The model of GPS-DR integrated navigation system is non-linear,the Extended Kalman Filter(EKF) used earlier made the integral property of the function be replaced by local property,and the performance of the system further degraded due to extra noise.The non-linear state estimation should be realized by Unscented Kalman Filter(UKF) method in order to acquire better performance.It is because the approximate process caused by linearization in EKF method is avoided,the algorithm's convergence speed and the loa...
Keywords:Integrated navigation EKF UKF Positioning precision  
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