An adaptive curvilinear model tracking algorithm based on the adaptive estimation of parameter
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This paper investigates an adaptive curvilinear model algorithm to track a highly maneuvering target which performs curvilinear motion. The target motion model is assumed to be a time-varying velocity curvilinear model with non-zero along-track and cross-track accelerations. The adaptive algorithm utilizes the filtering outputs to estimate the turn rate parameter and the along-track acceleration of this curvilinear model real-timely. It eliminates the performance limitation of the constant turn (CT) circular motion model which prescribes the target moves at a constant speed and a constant turn rate. The adaptive estimation of parameter enhances the tracking precision. Some simulations are carried out to test the performance of the adaptive algorithm and the results show the efficiency and feasibility of the proposed algorithm. (4 pages)