车载DR导航的非线性滤波方法研究  

Study on nonlinear filtering method for land vehicle DR navigation

作　　者：张传斌[1] 田蔚风[1] 金志华[1] 

机构地区：[1]上海交通大学仪器工程系,上海200030

出　　处：《系统工程与电子技术》2005年第6期1058-1060,1144,共4页Systems Engineering and Electronics

基　　金：中国博士后科学基金资助课题(20040350131)

摘　　要：针对扩展卡尔曼滤波方法(EKF)用于车载DR导航系统滤波中存在的一些缺点,将一种新的滤波方法—UKF滤波方法用于车载DR导航系统的非线性状态估计中。该滤波方法与EKF方法相比具有容易实现和滤波精度高的特点。通过非线性状态估计UKF方法大大提高了导航系统的精度。为了检验其有效性,将这两种方法分别对车载DR导航系统进行滤波仿真,仿真结果进一步表明UKF方法优于EKF方法,是一种理想的车载DR导航非线性滤波方法。In view of the problem that there exist some defects when the extended Kalman filter (EKF) is employed in the land vehicle deareckoning (DR) navigation a novel method-unscented Kalman filtering (UKF) is applied in the nonlinear state estimation of the land vehicle dead reckoning (DR) navigation. Compared with the EKF, the UKF has the characteristics of easier realization and higher state estimation accuracy. Through nonlinear state estimation, the UKF can improve the accuracy of the DR system greatly. In order to test the validity of the UKF, the two methods are used to estimate states of the land vehicle DR navigation system. Simulation results show that the UKF is superior to the EKF and is an ideal nonlinear filtering method in the land vehicle DR navigation.

关 键 词：车载导航 航位推算(DR) 非线性滤波 UKF 扩展卡尔曼滤波(EKF) 

分 类 号：V324[航空宇航科学与技术—人机与环境工程]