Tracking a maneuvering target in clutter with out-of-sequence measurements for airborne radar

There are many proposed optimal or suboptimal algorithms to update out-of-sequence measurement(s) (OoSM(s)) for linear-Gaussian systems, but few algorithms are dedicated to track a maneuvering target in clutter by using OoSMs. In order to address the nonlinear OoSMs obtained by the airborne radar located on a moving platform from a maneuvering target in clutter, an interacting multiple model probabilistic data association (IMMPDA) algorithm with the OoSM is developed. To be practical, the algorithm is based on the Earth-centered Earth-fixed (ECEF) coordinate system where it considers the effect of the platform's attitude and the curvature of the Earth. The proposed method is validated through the Monte Carlo test compared with the performance of the standard IMMPDA algorithm ignoring the OoSM, and the conclusions show that using the OoSM can improve the tracking performance, and the shorter the lag step is, the greater degree the performance is improved, but when the lag step is large, the performance is not improved any more by using the OoSM, which can provide some references for engineering application.