An MCMC-based Particle Filter for Tracking Target in Glint Noise Environment

In radar tracking application, the observation noise is highly non-Gaussian, which is also referred as glint noise. The performance of extended Kalman filter degrades severely in the presence of glint noise. In this paper, an improved particle filter, Markov chain Monte Carlo particle filter (MCMC-PF), is introduced to cope with radar target tracking in glint noise environment. The Monte Carlo simulation results show that MCMC-PF can efficiently track target both in Gaussian noise and glint noise environments.