A Low Computational Complexity JPDA Filter With Superposition

Angle R. B., Streit R. L., EFE M.

IEEE SIGNAL PROCESSING LETTERS, vol.28, pp.1031-1035, 2021 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 28
  • Publication Date: 2021
  • Doi Number: 10.1109/lsp.2021.3082040
  • Journal Name: IEEE SIGNAL PROCESSING LETTERS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.1031-1035
  • Keywords: Bayes methods, Computational complexity, Clutter, Target tracking, Probability distribution, Probability density function, Handheld computers, Multiple target tracking, JPDA, superposition, JPDAS, Bayesian estimator, point processes, intensity functions
  • Ankara University Affiliated: Yes

Abstract

Object superposition is a way to derive Bayesian estimators for multiple object tracking using point processes. A low computational complexity Bayesian multiple target tracking filter, based on target superposition, is presented. The concept of superposition is introduced and applied to the well-known Joint Probabilistic Data Association (JPDA) filter to derive the JPDA with superposition (JPDAS) filter. The JPDAS intensity function is evaluated to machine precision "for free" by computing the generating functional of the posterior process using complex arithmetic. A simulated example with eight targets is presented.