Abstract
This paper deals with the problem of tracking a target using an airborne AESA radar. Unlike the ground-based tracking systems, the angular motion of a platform makes the noise statistics of the converted measurements (CMs) complicated, hence the conventional approaches produce the biased target state estimates. To settle this problem, the predicted line-of-sight Cartesian coordinate system (PLCCS) is introduced. Provided that the a priori state estimation error is small enough, the statistical properties of the CMs in PLCCS can be accurately approximated only using the 1st and 2nd moments of the radar measurement noises. In addition, the resulting debiasing term leads to the satisfactory performance of the proposed filter. Enjoying the diagonal form of the noise covariance matrix, we can decouple the tracking filter into each axis for real-time implementation. Through simulations, the enhanced performance of the suggested method over the previous schemes is demonstrated.
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