Volume 48 Issue 12
Dec.  2022
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WU Sunyong, ZHOU Yusong, XIE Yun, et al. Extended target tracking algorithm based on MM-GGIW-PMBM filter[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(12): 2356-2364. doi: 10.13700/j.bh.1001-5965.2021.0162(in Chinese)
Citation: WU Sunyong, ZHOU Yusong, XIE Yun, et al. Extended target tracking algorithm based on MM-GGIW-PMBM filter[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(12): 2356-2364. doi: 10.13700/j.bh.1001-5965.2021.0162(in Chinese)

Extended target tracking algorithm based on MM-GGIW-PMBM filter

doi: 10.13700/j.bh.1001-5965.2021.0162
Funds:

National Natural Science Foundation of China 62263007

National Natural Science Foundation of China 62061010

National Natural Science Foundation of China 62161007

Central Government Guided Local Science and Technology Development Fund Project 2022ZYZX2001

Gaungxi Natural Science Foundation 2019GXNSFBA245072

Director Fund of Guangxi Key Laboratory of Precision Navigation Technology and Application 

Innovation Training Program for College Students 201910595164

Innovation Project of GUET Graduate Education 

More Information
  • Corresponding author: WU Sunyong, E-mail: wusunyong121991@163.com
  • Received Date: 01 Apr 2021
  • Accepted Date: 03 Jul 2021
  • Publish Date: 30 Jul 2021
  • To address the problem of multiple maneuvering extended target tracking, this paper introduces the concept of interactive multiple models into the Poisson multi-Bernoulli mixture filtering (PMBM) algorithm, and proposes a multi-model algorithm with Gamma Gaussian inverse Wishart and PMBM (MM-GGIW-PMBM). Firstly, the algorithm integrates multiple motion models and realizes the hybrid estimation and prediction of the extended state of the maneuvering target and the centroid state through the interaction of the models. Secondly, the covariance matrix in the predicted GGIW components is modified by introducing the fading factor into the strong tracking filter (STF) to prevent the tracking model mismatch. Finally, the target shape is expanded in the PMBM update stage based on the completion of centroid estimation, and the likelihood function is used to update the model probability. The simulation shows that the proposed algorithm can effectively estimate the number and state of multiple maneuvering extended targets.

     

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  • [1]
    GRANSTRÖM K, BAUM M. Extended object tracking: Introduction, overview and applications[J]. Journal of Advances in Information Fusion, 2017, 12(2): 140-174.
    [2]
    MAHLER R. Multitarget Bayes filtering via first-order multitarget moments[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(4): 1152-1178. doi: 10.1109/TAES.2003.1261119
    [3]
    VO B N, MA W K. The Gaussian mixture probability hypothesis density filter[J]. IEEE Transactions on Signal Processing, 2006, 54(11): 4091-4104. doi: 10.1109/TSP.2006.881190
    [4]
    CLARK D, VO B N. Convergence analysis of the Gaussian mixture PHD filter[J]. IEEE Transactions on Signal Processing, 2007, 55(4): 1204-1212. doi: 10.1109/TSP.2006.888886
    [5]
    MAHLER R. PHD filters of higher order in target number[J]. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(4): 1523-1543. doi: 10.1109/TAES.2007.4441756
    [6]
    PASHA S A, VO B N, TUAN H D. A Gaussian mixture PHD filter for jump Markov system models[J]. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(3): 919-936. doi: 10.1109/TAES.2009.5259174
    [7]
    SHEN X, SONG Z, FAN H, et al. Particle filter implementation of CPHD filter for unknown clutter[C]//2017 6th International Conference on Electrical Engineering and Informatics. Pisca-taway: IEEE Press, 2017: 1-6.
    [8]
    VO B T, VO B N. Labeled random finite sets and multi-object conjugate priors[J]. IEEE Transactions on Signal Processing, 2013, 61(13): 3460-3475. doi: 10.1109/TSP.2013.2259822
    [9]
    VO B T, VO B N. The labeled multi-Bernoulli filter[J]. IEEE Transactions on Signal Processing, 2014, 62(12): 3246-3260. doi: 10.1109/TSP.2014.2323064
    [10]
    GRANSTRÖM K, FATEMI M, SVENSSON L. Poisson multi-Bernoulli mixture conjugate prior for multiple extended target filtering[J]. IEEE Transactions on Aerospace and Electronic Systems, 2020, 56(1): 208-225. doi: 10.1109/TAES.2019.2920220
    [11]
    GRANSTRÖM K, ORGUNER U. On spawning and combination of extended/group targets modeled with random matrices[J]. IEEE Transactions on Signal Processing, 2013, 61(3): 678-692. doi: 10.1109/TSP.2012.2230171
    [12]
    MAZOR E, AVERBUCH A, BAR-SHALOM Y, et al. Interacting multiple model methods in target tracking: A survey[J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(1): 103-123. doi: 10.1109/7.640267
    [13]
    甘林海, 刘进忙, 王刚, 等. 多模型GGIW-GLMB算法跟踪机动群目标[J]. 北京航空航天大学学报, 2018, 44(10): 2185-2192. doi: 10.13700/j.bh.1001-5965.2018.0053

    GAN L H, LIU J M, WANG G, et al. Multi model GGIW-GLMB algorithm for tracking maneuvering group targets[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(10): 2185-2192(in Chinese). doi: 10.13700/j.bh.1001-5965.2018.0053
    [14]
    汪云, 胡国平, 甘林海. 基于多模型GGIW-CPHD滤波的群目标跟踪算法[J]. 华中科技大学学报(自然科学版), 2017, 45(2): 89-94. https://www.cnki.com.cn/Article/CJFDTOTAL-HZLG201702017.htm

    WANG Y, HU G P, GAN L H. Group target tracking algorithm based on multi model GGIW-CPHD filtering[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2017, 45(2): 89-94(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HZLG201702017.htm
    [15]
    RAHMATHULLAH A S, GARCÍA-FERNÁNDEZ Á F, SVENSSON L. Generalized optimal sub-pattern assignment metric[C]//2017 20th International Conference on Information Fusion. Piscataway: IEEE Press, 2017: 1-8.
    [16]
    GRANSTRÖM K, LUNDQUIST C, ORGUNER U. A Gaussian mixture PHD filter for extended target tracking[C]//2010 13th International Conference on Information Fusion. Piscataway: IEEE Press, 2010: 1-8.
    [17]
    YANG S, BAUM M, GRANSTRÖM K. Metrics for performance evaluation of elliptic extended object tracking methods[C]//2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. Piscataway: IEEE Press, 2016: 523-528.
    [18]
    GIVENS C R, SHORTT R M. A class of Wasserstein metrics for probability distributions[J]. Michigan Mathematical Journal, 1984, 31(2): 231-240.
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