A new particle filtering algorithms applied to GPS/DR integrated navigation
In allusion to the fact of GPS/DR integrated navigation system, several popular improved algorithms to the particle filtering are analyzed and compared systematically and thoroughly, and after that, a new particle filtering algorithm applied to GPS/DR integrated navigation called the adaptive fading extended Kalman particle filter is proposed in this paper.This method takes advantage of the fading extended Kalman filter to generate the proposal distribution function, and can tune the parameter online, which has better adaptability and robustness.Compared with several improved particle filtering methods, whose proposal distribution fimctions coming from the transition prior, the extended Kalman filter, the adaptive extended Kalman filter, the iterated extended Kalman filter and the unscented Kalman filter, the new algorithm improves the accuracy of the particle filtering.An experiment upon the GPS/DR integrated navigation system is carried out to validate the effectiveness of the approach.
GPS/DR particle filter fading filter forgetting factor extended Kalman filter unscented Kalman filter
Yi-Song Gong Qing-Ming Gui Bao-Li Li Jin-Jun Zhang
Institute of Surveying and Mapping, Information Engineering University, No.66, Middle Longhai Road, Institute of Science, Information Engineering University, No.62, Kexue Road, 450001, Zhengzhou, P.R. Branch 22 of unit 92493, 125000, Huludao, P.R.China
国内会议
北京
英文
1402-1411
2010-05-19（万方平台首次上网日期，不代表论文的发表时间）