Fast Adaptive Update Rate for Phased Array Radar Using IMM Target Tracking Algorithm

摘要

The capability of a Phased Array Radar to use an adaptive sampling policy by the agile beam positioning results in an adaptive selection of the sampling time interval which improves the tracking performance. This paper presents a simple fast algorithm to determine the next update time for track update in Phased Array Radar. This algorithm is based on the Interacting Multiple Models (IMM) algorithm which is appropriate for maneuvering targets tracking. The IMM is used here to predict and estimate the target's possible states and to select the correct next update time. The idea is to assign to each model in the MM algorithm an appropriate rate and to weight these rates by the models' probabilities to obtain the rate to use. The resulting algorithm is named the Fast Adaptive Interacting Multiple Models (FAIMM algorithm). The performances of this algorithm are compared to that of the Adaptive IMM algorithm that uses Van Keuk criterion to select the next update time and to that of the IMM algorithm that uses a constant update time.