| Citation: | LU Xiaoke, ZHANG Zhiguo, SUN Jinping, et al. An improved multi-sensor MeMBer filter based on clutter measurement set constraint[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(9): 1748-1755. doi: 10.13700/j.bh.1001-5965.2020.0317(in Chinese)
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To solve the problems existing in the traditional Multi-Sensor Multi-Target Multi-Bernoulli (MS-MeMBer) filter in the high clutter density scene, such as poor quality of measurement partitioning hypothesis and biases of cardinality estimation, an improved MS-MeMBer filter based on clutter measurement set constraint is proposed. By introducing the influence of the clutter measurement set into the update step, the weight of the target measurement set is optimized and the single target multi-sensor likelihood function in the clutter scene is given. After that, the improved multi-sensor measurement partitioning hypothesis is obtained by two-step greedy partition mechanism. The proposed method is compared with the traditional MS-MeMBer filter by simulation. The experimental results show that the proposed method has better multi-target tracking performance in high clutter density scene.
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