Target tracking in glint noise environment using nonlinear non-Gaussian Kalman filter

The problem of nonlinear non-Gaussian target tracking with glint measurement noise is addressed in this work. The heavy-tailed glint noise distribution is modeled by mixture of two Gaussians. A new nonlinear Gaussian mixture Kalman filter (NL-GMKF), is applied to this problem. The tracking performance of the NL-GMKF is evaluated and compared to the particle filter (PF) and the extended Kalman filter (EKF) via simulations. It is shown that the NL-GMKF outperforms both the PF and the EKF.