Abstract:

Two important uncertain factors for tracking ballistic reentry targets by a ground based radar will result in big filtering bias. One is that the ballistic coefficient is usually unknown; the other is the uncertain process noise matrix. In order to resolve the problem, the paper adopts an iterative multiplemodel unscented filter (IMM UF) to track ballistic reentry targets, and chooses the models with different ballistic coefficients and different process noise matrices as the components of the model bank. The paper compares the simulation results of IMM UF with those of extended Kalman filter (EKF) and UF, and then compares the filtering performances of IMM UF and autonomous multiple model (AMM) UF. The simulation results prove that the proposed method can track the ballistic reentry targets without prior information more precisely.