Particle filter based target tracking in non-Gaussian environment

Particle filter is a new filtering method based on Bayesian estimation and Monte Carlo method and can effectively cope with complicated nonlinear and/or non-Gaussian problems. The basic idea and algorithm description of particle filter were presented. Then, particle filter was introduced to radar tracking based on the glint noise statistical model. The Monte Carlo simulation results show that in Gaussian environment both extended Kalman filter and particle filter have almost the same tracking accuracy, and that in glint noise environment particle filter has also good accuracy, while the extended Kalman filter's performance degrades severely as the glint effect increasing.