关键词: 组合导航, Sage-husa自适应卡尔曼滤波, 非完整约束, 前向导航, 后向导航, 加权组合滤波算法

Abstract: MEMS IMU/GPS integrated navigation system application environments have become increasingly complex, and higher and higher accuracy has been required. Using only the ordinary Kalman filter can’t meet the requirements of accuracy and stability. For this problem, the Sage-husa adaptive Kalman filter algorithm and nonholonomic constraints are applied to the forward and backward navigation filtering algorithm, and the results of the forward and back navigation filtering algorithm are weighted combination. A weighted combination filtering algorithm is proposed with nonholonomic constraint, which is used in the post-IMU/GPS combination solution, and which is used for improving navigation accuracy. And laboratory equipment is used to do vehicle experiments. The measured vehicle data solution results validate the feasibility of the method. Experimental results show that the MEMS IMU/GPS combination filtered latitude and longitude error is less than 1.4 m, and heading angle error is less than 1.0°, which meet MEMS IMU/GPS vehicle navigation system accuracy requirements.

Key words: integrated navigation, Sage-husa adaptive Kalman filter, nonholonomic constraints, forward navigation, backward navigation, weighted combination filtering algorithm