13 October 2008 An improved adaptive tracking algorithm based on "current" statistical model
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Abstract
In order to track aerial target using data from radars, we improved an adaptive extended Kalman filtering algorithm based on "Current" Statistical Model. In this improved algorithm, the interval of acceleration probability distribution is adjusted, and Singer model is adopted instead of "Current" Statistical Model when target in the low-level maneuver. According to the real-time estimation of acceleration and its change rate, self-adaption of extremum of acceleration is achieved. Based on the Monte Carlo simulation, we got the conclusion that aerial target in different maneuver situation can be tracked quickly, especially in the low-level maneuver, the improvement of tracking precision is notable.
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Mei Yuan, Mei Yuan, Jiong Chen, Jiong Chen, Xu Liang, Xu Liang, } "An improved adaptive tracking algorithm based on "current" statistical model", Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 71281K (13 October 2008); doi: 10.1117/12.806723; https://doi.org/10.1117/12.806723
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