Data Fusion Algorithm for INS/GPS/Odometer Integrated Navigation System

摘要：

INS/GPS/Odometer are commonly integrated using a federated Kalman filter to provide a robust navigation solution, overcoming their weaknesses. However, the accuracy of federated Kalman filter is degraded in the condition that the statistical characteristics of noise dont be known accurately. The method of federated Kalman filter is improved to perform the INS/GPS/Odometer integrated navigation in this paper. This method uses fuzzy adaptive Kalman filter to detect changes of the measurement noise statistical characteristics and correct them gradually. Meanwhile, weighted coefficient is used to describe the degree of confidence of sub-filters. Simulations in INS/GPS/Odometer integrated navigation system demonstrate that the weighted coefficients of sub-filters with low confidence are decreased adaptively, and the accuracy is improved compared with the federated kalman filter.

作者: Pingyuan CUI Tianlai XU

作者单位: Harbin Institute of Technology, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）