Multi-target Tracking and Track Management Algorithm Based on UFIR Filter With Imperfect Detection Probability

Chang Joo Lee, Sang Kyoo Park, Myo Taeg Lim

Research output: Contribution to journalArticle

Abstract

This paper proposes an unbiased finite impulse response filter and track management algorithm for multi-target tracking (MTT) with imperfect detection probability. Targets cannot be detected under MTT for various reasons, including sensor failure and screening by other targets. Despite the temporary missed detection, the proposed MTT algorithm robustly tracks targets under MTT conditions by replacing the missed detection with recently detected target measurement. The track is deleted on the track table when consecutive detection failure exceeding missing horizon occurs. Computational time for the proposed MTT algorithm is significantly less than that for existing MTT algorithm based finite impulse response filters due to the proposed track update and track management algorithm. Simulation and experimental vehicle and pedestrian tracking results verify outstanding tracking accuracy and shorter calculation times for the proposed algorithm.

Original languageEnglish
Pages (from-to)3021-3034
Number of pages14
JournalInternational Journal of Control, Automation and Systems
Volume17
Issue number12
DOIs
Publication statusPublished - 2019 Dec 1

Keywords

  • Finite impulse response structure
  • imperfect detection probability
  • missing horizon
  • multi-target tracking
  • track management
  • unbiased filtering

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications

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