Study on SINS/GPS Tightly Integrated Navigation Based on Adaptive Extended Kalman Filter

摘要：

This paper presents a novel SINS/GPS tightly integrated navigation algorithm based on Adaptive Extended Kalman Filtering. This algorithm is mainly used in vehicle SINS/GPS integrated navigation system to deal with time varied noise statistic in different working conditions. First, measurement noise covariance is estimated through innovation sequence online, then the covariance matching algorithm is used to track the process noise real-time based on the system equation. More, scale factor is introduced to reduce truncation error caused by Taylor formulation and thus improve estimation accuracy. The Simulations results show that, compared with the traditional extended kalman filter algorithm and unscented kalman filter algorithm, the proposed algorithm is able to estimate the changes of both process and observation noise statistics simultaneous, and have higher precision and more robustness.

关键词： Extended Kalman Filter Adaptive Extended Kalman Filter SINS/GPS Noise Estimation on-Line Covariance Matching

作者: Weidong Zhou Xiang-wei Qiao Fanbin Meng Hebing Zhang

作者单位: College of Automation Harbin Engineering University Harbin,150001,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-4

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）