Research on Integrated Navigation Technology of Field Robot
This paper introduced GPS/INS integrated navigation technology into field robot navigation system, and mainly discussed the data fusion algorithm based on fuzzy adaptive Kalman filter. For the reason that classical Kalman filter might lead to divergence of system state parameter estimation when it dealt with time varied statistic of measurement noise in different working conditions, then by monitoring the variation grade of the actual residual compared with filter residual, the novel algorithm could adjust recursively the measurement noise covariance of Kalman filter online to make it close to real measurement covariance gradually. As a result, the Kalman filter performs optimally and the accuracy of the navigation system is improved. The simulation result also proves that this fuzzy adaptive Kalman filter works better than the conventional filtering algorithm.
navigation data fusion Kalman filter fuzzy adaptive filter.
Feng-chun ZHU Yan-bing JU Ai-hua WANG
School of Information and Electrical Engineering Shandong University of Science and Technology Qingd School of Management and Economics Beijing Institute of Technology Beijing, China
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
59-64
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）