| Citation: | YOU Hanghang, HAN Qisong, YU Minjian, et al. Target tracking algorithm based on AIGWO-IMMUKF[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(10): 1826-1833. doi: 10.13700/j.bh.1001-5965.2019.0405(in Chinese)
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Aimed at the problem of filter selection and model design in target tracking algorithm, an adaptive Interacting Multiple Model-Unscented Kalman Filter (IMMUKF) target tracking algorithm is proposed. First, the algorithm steps of IMMUKF are introduced. Second, the Improved Grey Wolf Optimizer (IGWO) is proposed to optimize the filter parameters, and the time-varying Markov state transition probability is established by constructing the adjustment factor. Then, the AIGWO-IMMUKF algorithm is formed and its algorithm flowchart is given. Finally, the AIGWO-IMMUKF algorithm proposed in this paper and the traditional method are simulated under the same conditions, and the root mean square error curves of position and velocity as well as the timeliness comparison chart are obtained. The results show that AIGWO-IMMUKF algorithm overcomes the shortcomings of traditional IMMUKF, improves the performance of the algorithm, and has better accuracy and timeliness.
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