An Improved Real-time Adaptive Kalman Filter For Low-Cost Integrated GPS/INS Navigation

摘要：

Recent years, we have witnessed a significant progress in integrated Global Positioning System (GPS)/ Inertial Navigation System (INS) navigation systems. In such systems, Kalman filter has been playing a key role in fusing data from multiple sensors for better accuracy. Despite the success, there is still a strong need for costefficient solutions with acceptable precision. One of the essential challenges for such demand is that, conventional Kalman filters tend to diverge when constant noise covariance matrices no longer match the error estimation of low-cost devices. To deliver a higher level of accuracy and stability, adaptive Kalman filters have attracted considerable research effort Based on the analysis of two recent adaptive Kalman filters, we propose an improved real-time adaptive algorithm with fuzzy logic adaptive tuning to achieve high accuracy on cost-efficient GPS/INS devices. A GPS data validation method is also introduced to reject corrupted GPS data. Real road experimental results prove that the proposed improved adaptive algorithm offers higher overall system performance.

关键词： GPS/INS integration adaptive Kalman filter GPS data validation fuzzy logic real-time positioning

作者: Enbo Shi

作者单位: Institute of Microelectronic, Department of Electronics Tsinghua University Beijing, China

会议类型: 国际会议

会议名称: 2012 International Conference on Measurement,Information and Control(2012测量、信息与控制国际会议 ICMIC2012)

会议地点: 哈尔滨

会议语种:英文

页码: 1070-1075

在线出版日期: 2012-05-18（万方平台首次上网日期，不代表论文的发表时间）