Volume 32 Issue 5
Sep.  2023
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DU Haocui, XIE Weixin, LIU Zongxiang, et al., “Track-Oriented Marginal Poisson Multi-Bernoulli Mixture Filter for Extended Target Tracking,” Chinese Journal of Electronics, vol. 32, no. 5, pp. 1106-1119, 2023, doi: 10.23919/cje.2021.00.194
Citation: DU Haocui, XIE Weixin, LIU Zongxiang, et al., “Track-Oriented Marginal Poisson Multi-Bernoulli Mixture Filter for Extended Target Tracking,” Chinese Journal of Electronics, vol. 32, no. 5, pp. 1106-1119, 2023, doi: 10.23919/cje.2021.00.194

Track-Oriented Marginal Poisson Multi-Bernoulli Mixture Filter for Extended Target Tracking

doi: 10.23919/cje.2021.00.194
Funds:  This work was supported by the National Natural Science Foundation of China (61271107, 61703280, 62171287) and the Shenzhen Basic Research Project (JCYJ20170818102503604)
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  • Author Bio:

    Haocui DU was born in 1986. She reveived the Ph.D. degree from Shenzhen University, Shenzhen, China. Her main research interests include radar target tracking and intelligent information processing. (Email: hcdu@szu.edu.cn)

    Weixin XIE was born in 1941. He received the B.S. degree from Xidian University, Xi’an, China, and joined the faculty of Xidian University in 1965. From 1981 to 1983, he was a Visiting Scholar with University of Pennsylvania, USA. In 1989, he was invited to University of Pennsylvania as a Visiting Professor. He is currently a Professor with Shenzhen University. His main research interests include intelligent information processing, fuzzy information processing, image processing, and pattern recognition. (Email: wxxie@szu.edu.cn)

    Zongxiang LIU (corresponding author) was born in 1965. He received the Ph.D. degree from Xidian University, Xi’an, China. He is currently a Professor of College of Electronic and Information Engineering, Shenzhen University. His research interests include multi-sensor information fusion, multiple target tracking, and random set theory. (Email: liuzx@szu.edu.cn)

    Liangqun LI was born in 1979. He is currently a Professor of College of Information Engineering, Shenzhen University. He visited the University of New Orleans (UNO) as a Visiting Research Scientist from 2017 to 2018. His research interests include signal processing, fuzzy sets, information fusion, and target tracking. (Email: lqli@szu.edu.cn)

  • Received Date: 2021-05-26
  • Accepted Date: 2021-10-21
  • Available Online: 2022-03-05
  • Publish Date: 2023-09-05
  • In this paper, we derive and propose a track-oriented marginal Poisson multi-Bernoulli mixture (TO-MPMBM) filter to address the problem that the standard random finite set filters cannot build continuous trajectories for multiple extended targets. First, the Poisson point process model and the multi-Bernoulli mixture (MBM) model are used to establish the set of birth trajectories and the set of existing trajectories, respectively. Second, the proposed filter recursively propagates the marginal association distributions and the Poisson multi-Bernoulli mixture (PMBM) density over the set of alive trajectories. Finally, after pruning and merging process, the trajectories with existence probability greater than the given threshold are extracted as the estimated target trajectories. A comparison of the proposed filter with the existing trajectory filters in two classical scenarios confirms the validity and reliability of the TO-MPMBM filter.
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