Adaptive Auxiliary Particle Filter for Track-Before-Detect With Multiple Targets

Research output: Contribution to journalArticle

Researchers

  • Luis Ubeda-Medina
  • Angel F. Garcia-Fernandez
  • Jesus Grajal

Research units

  • Polytechnic University of Madrid

Abstract

A novel particle filter for multiple target tracking with track-before-detect measurement models is proposed. Particle filters efficiently perform target tracking under nonlinear or non-Gaussian models. However, their application to multiple target tracking suffers from the curse of dimensionality. We introduce an efficient particle filter for multiple target tracking which deals with the curse of dimensionality better than previously developed methods. The proposed algorithm is tested and compared to other multiple target tracking particle filters.

Details

Original languageEnglish
Article number7894277
Pages (from-to)2317-2330
Number of pages14
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume53
Issue number5
Publication statusPublished - Oct 2017
MoE publication typeA1 Journal article-refereed

    Research areas

  • MULTITARGET TRACKING, CONVERGENCE RESULT, BAYESIAN-APPROACH

ID: 16141338