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Distributed Lattice Smooth Variable Structure Filter for Target Tracking Under Model Uncertainty

  • Yuzhao Jiao
  • , Jianxiong Niu
  • , Hongmei Zhao*
  • , Taishan Lou
  • , Liangyu Zhao
  • *Corresponding author for this work
  • Zhengzhou University of Light Industry

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The conventional filters algorithm cannot provide a stable and precise state estimation for target tracking in Air Traffic Control (ATC) with motion model uncertainty. In this paper, the new filter and distributed fusion strategies are proposed. First, a Lattice Smooth Variable Structure Filter (LSVSF) is proposed for nonlinear system with model uncertainty, which avoids the calculation of Jacobi matrices. Then, the distributed lattice smooth variable structure filter Distributed Lattice Smooth Variable Structure Filter (MW-LSVSF) is proposed, and the cross-covariance of local estimators is calculated by lattice sampling. Finally, the state estimation accuracy and robustness are verified by ATC scenarios.

Original languageEnglish
Title of host publicationProceedings - 2023 38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages552-556
Number of pages5
ISBN (Electronic)9798350303636
DOIs
Publication statusPublished - 2023
Event38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023 - Hefei, China
Duration: 27 Aug 202329 Aug 2023

Publication series

NameProceedings - 2023 38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

Conference

Conference38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023
Country/TerritoryChina
CityHefei
Period27/08/2329/08/23

Keywords

  • distributed fusion
  • smooth variable structure filter
  • state estimation
  • target tracking

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