一种用于GPS/DR组合定位的非线性滤波算法

建立了适用于车辆导航系统的基于UKF(Unscented Kalman Filter)的GPS/DR(Global Positioning System/Dead Reckoning)组合定位滤波模型及算法.针对系统状态方程为线性、观测方程为非线性的特点,提出了一种将UKF和EKF(Extended Kalman Filter)相结合的非线性滤波算法.结合后的算法和原有UKF算法相比减少了在时间更新阶段的运算量,并且由于采用基于Unscented变换的思想来处理系统观测方程的非线性问题,避免了EKF引入的线性化误差,提高了滤波精度.仿真结果证明:算法在减少运算量的同时,仍具有较高的滤波精度,且明显优于EKF,因而能够满足车辆导航系统占用资源少、滤波精度高的要求.

Nonlinear filter algorithm for GPS/DR integrated positioning

A filter model and its algorithm based on UKF(unscented Kalman filter) for GPS/DR(global positioning system/dead reckoning) integrated positioning in land vehicle navigation system were established.Aiming at the system characteristic of linear state equation and nonlinear measurement equation,the algorithm which combines UKF with EKF(extended Kalman filter) was proposed.Compared with general UKF,the operation time used for the phase of time updating is less than that of general UKF.The error caused by the linearization of EKF is eliminated and the precision is improved contributing to processing the nonlinear problem with unscented transform.The simulation result demonstrates that the algorithm has better filtering precision than EKF,and reduces computing time,which is fit for integrated navigation system demanding for little resource and high precision.