Tracking refractivity from radar clutter using particle filter
利用粒子滤波从雷达回波实时跟踪反演大气波导

Particle filter(PF) is an effective algorithm for the state recursive estimation in nonlinear and non-Gaussian dynamic systems by utilizing the Monte Carlo simulation, and it is applicable for solving the nonlinear and non-Gaussian RFC(refractivity from radar clutter) problems. The basic idea and the specific algorithm of PF are introduced; the implementation of the iterative inversion algorithm is derived finally. The experimental result indicates that the particle filter is suited to solve the nonlinear inversion problem and can effectively increase the stability and the accuracy of inversion results compared with the extended Kalman filter (EKF) and the unscented kalman filter (UKF).