• Electronics Optics & Control
  • Vol. 30, Issue 10, 46 (2023)
SONG Wei1 and LI Chunju2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2023.10.008 Cite this Article
    SONG Wei, LI Chunju. Adaptive Random Weighted Cubature Kalman Filter and Interactive Multiple Model Algorithm for Target Tracking[J]. Electronics Optics & Control, 2023, 30(10): 46 Copy Citation Text show less

    Abstract

    To tackle the problem of complex maneuvering target tracking,an algorithm of Adaptive Random Weighted Cubature Kalman Filter (ARWCKF) is proposed.As the preprocessing process of Interactive Multiple Model (IMM) algorithm,this algorithm conducts filtering on different motion models.In order to improve the stability of the algorithm,a random weighted factor is introduced.A time-varying factor is used to adjust Markov probability transfer matrix,which improves the probability conversion accuracy of IMM algorithm.Compared with IMM-CKF algorithm,the proposed IMM-ARWCKF algorithm has higher tracking accuracy and better stability in dealing with complex maneuvering targets.
    SONG Wei, LI Chunju. Adaptive Random Weighted Cubature Kalman Filter and Interactive Multiple Model Algorithm for Target Tracking[J]. Electronics Optics & Control, 2023, 30(10): 46
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