ADAPTIVE FADING EXTENDED KALMAN PARTICLE FILTERING APPLIED TO INTEGRATED NAVIGATION
Gong Yisong 1) ;Gui Qingming 2) ;Li Baoli 1) ; and Wang Junjiang 3)
1)Institute of Surveying and Mapping, PLA Information Engineering University, Zhengzhou 4500522)Institute of Science, PLA Information Engineering University, Zhengzhou 4500013)61365 Troops, Tianjin 300140
Abstract In respect to the degradation of the weight existing in the particle filtering, from the point of view of the proposal distribution function, a new particle filtering method named the adaptive fading extended Kalman particle filtering is put forward. This method takes advantage of the adaptive fading extended Kalman filter to generate the proposal distribution function, and can adjust the parameter on line, which has better self adaptability and robustness. Compared with the common particle filtering methods whose proposal distribution function coming from the transition prior or the extended Kalman filtering, the adaptive fading extended Kalman particle filter has improved the accuracy of the particle filtering.
