Maximum Correntropy-Based Extended Particle Filter for Nonlinear System

Yongze Jin, Lingxia Mu, Nan Feng, Xinhong Hei, Yankai Li, Guo Xie, Xin Ye, Jiajie Li

Abstract: To solve the particle degradation and sample impoverishment, a maximum correntropy-based extended particle filter method is proposed by optimizing the important density function. In the proposed method, the importance sampling is guided by the measurement information, the entropy criterion and high-order moments information of the signal are fully utilized, and the non-Gaussian heavy-tailed distribution noise and the noise with outliers are effectively suppressed. The simulation results demonstrate the effectiveness and feasibility of the filtering method.