A new particle filter with GA-MCMC resampling
Cuiyun Li, Hongbing Ji · 2007
Particle filtering shows great promise in addressing a wide variety of non-linear and/or non-Gaussian problem. A crucial issue in particle filtering is to remove degeneracy phenomenon and alleviate the sample impoverishment problem. In this paper, Variations, using techniques from the genetic algorithm with Markov Chain Monte Carlo mutation, to standard PF procedures are proposed to solve these problem simultaneously. The simulation results show that the new particle filter superiors to the standard particle filter and the other filters.