Adaptive Robust Unscented Particle Filter and its Application in SINS/SAR Integration Navigation System
This paper presents a new robust adaptive unscented particle filtering algorithm by adopting the concept of the adaptive robust filtering to the unscented particle filter.This algorithm adaptively determines the equivalent weight function and adaptively adjusts the adaptive factor constructed from predicted residuals to resist the disturbances of singular observations and the kinematic model noise,thus preventing particles from degeneracy.It also uses the unscented transformation to improve the accuracy of particle filtering,thus providing the reliable state estimation for improving the performance of adaptive robust filtering.Experiments and comparison analysis demonstrate that the proposed filtering algorithm can effectively resist disturbances due to system state noise and observation noise,and the filtering accuracy is much higher than the extended Kalman filter,unscented Kalman filter,standard particle filter and unscented particle filter.
Unscented transformation unscented particle filter adaptive robust filtering equivalent weight function adaptive factor
Haifeng Yan Xuehua Zhao Shesheng Gao Jing Zhang Xiaoyuan Shao
School of Automatics,Northwestern Polytechnical University,Xian,China School of Automatics,Northwestern Polytechnical University,Xian,China;Department of Mathematics and
国际会议
重庆
英文
2364-2368
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）