Comparison of Nonlinear Filtering for Passive Bistatic Radar Target Tracking
Zengping Chen · Jisuanji fangzhen · 2008
For passive bistatic radar target tracking problem, the performances of several nonlinear filtering algorithms such as EKF, UKF and CDF were simulated and analyzed. Also, a new nonlinear filtering algorithm called BSUKF/CDF based on backward-smoothing principle was proposed. In BSUKF/CDF algorithm, the current observation was used to smoothly estimate the previous mean and covariance of the state variable. The simulation results show that in Gaussian environment, BSUKF/CDF and UKF/CDF have almost the same tracking performance, and both perform better than EKF; however in angle glint noise environment, BSUKF/CDF perform much better than UKF/CDF and EKF.