关键词: 卡尔曼滤波, 状态估计, 西格马点

Abstract: In view of the defects when extended Kalman Filter is employed in the nonlinear land vehicle system, this paper introduces a new method—Sigma Point Kalman Filter in the navigation state estimation problem. The idea of the filter is based on weighted statistical linear regression technology, the SPKF can generate better estimates of mean and the covariance of the state. Compared with the filtering estimate results given from a time series state estimation example based on GPS/DR Model navigation sysytem, the simulation shows that SPKF not only leads to more accurate results than EKF, but also avoid computing Jacobi matrix. So it is an ideal nonlinear filtering method in the land vehicle navigation.

Key words: Kalman Filter, State estimation, Sigma points