关键词: 粒子滤波, 状态估计, UKF, 自适应滤波, 强跟踪滤波器

Abstract:

This paper analyzes the keys for the performance of particle filter(PF)and presents a new adaptive PF algorithm.The algorithm adopts a new proposal distribution combining the unscented Kalman filter(UKF)with the adaptive strong tracking filter(STF).The new proposal distribution adopts UKF to produce the particles,in which each sigma point of every particle is updated by STF.Moreover,the added scaling factor can be adjusted on line to
make the algorithm adaptive.Simulated experiments of nonlinear state estimation are finally ca~ied out to confirm the validity of the improved PF algorithm.

Key words: particle filter, state estimation, unscented Kalman filter, adaptive filtering, strong tracking filter