Tracking of Maneuvering Targets with Poisson Labeled multi-Bernoulli Tracker

Guchong Li, Tiancheng Li

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

Abstract

In this paper, the Poisson labeled multi-Bernoulli (PLMB) tracker is exploited to solve the problem of maneuvering target tracking. For avoiding tracking divergence resulting from a single motion model, multiple models (MM) strategy is applied to the PLMB tracker. Specifically, each state of target is coupled with all possible motion models and the model transition is considered throughout the tracking process. Simulation results demonstrate that the proposed MM-PLMB tracker strikes a favorable balance between limited computational resources and high tracking accuracy when compared to state-of-the-art approaches.

Original languageEnglish
Title of host publicationProceedings - 12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023
EditorsTruong Xuan Tung, Tran Cong Tan, Cao Huu Tinh
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages109-114
Number of pages6
ISBN (Electronic)9798350328783
DOIs
StatePublished - 2023
Event12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023 - Hanoi, Viet Nam
Duration: 27 Nov 202329 Nov 2023

Publication series

NameProceedings - 12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023

Conference

Conference12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023
Country/TerritoryViet Nam
CityHanoi
Period27/11/2329/11/23

Keywords

  • jump Markov system
  • maneuvering target tracking
  • multiple models
  • Poisson labeled multi-Bernoulli

Fingerprint

Dive into the research topics of 'Tracking of Maneuvering Targets with Poisson Labeled multi-Bernoulli Tracker'. Together they form a unique fingerprint.

Cite this