A survey of PHD filter based multi-target tracking

Feng Yang, Yong Qi Wang, Yan Liang, Quan Pan

Research output: Contribution to journalReview articlepeer-review

28 Scopus citations

Abstract

Probability hypothesis density (PHD) filter has attracted much attention in multi-target tracking, traffic control, image processing, multi-sensor management and other fields. An overview of the emergence, the development and the present research situation of the PHD filter in target tracking is presented here. Special attention is paid to the following areas: PHD filter, its implementation method, the peak and track extraction technology, multi-sensor multi-target tracking, multi-sensor management, PHD smoother, the assessment metrics of multi-target tracking performance, and also the relevant applications. Finally, based on the progress of existing PHD filters, some key issues which need to be focused on for PHD filters in multi-target tracking are introduced.

Original languageEnglish
Pages (from-to)1944-1956
Number of pages13
JournalZidonghua Xuebao/Acta Automatica Sinica
Volume39
Issue number11
DOIs
StatePublished - Nov 2013

Keywords

  • Bayes filter
  • Multi-target tracking
  • Peak and track extraction
  • Probability hypothesis density (PHD)

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