Data association for target tracking rooted in maximum-likelihood values

作者：Santos Eduardo^*; Haykin Simon

来源：IET Radar Sonar and Navigation, 2018, 12(2): 195-201.

DOI：10.1049/iet-rsn.2017.0162

• target tracking
• maximum likelihood estimation
• sensor fusion
• probabilistic data association
• PDA
• target tracking
• maximum-likelihood values
• measurement uncertainty conditions
• computer simulations
• track loss reduction

A modified version of the probabilistic data association (PDA) is proposed for target tracking under measurement uncertainty conditions. This method uses the likelihood of each validated measurement, and selects the best k candidates to be integrated with the PDA. Different computer simulations with a single target under dense-cluttered environment are presented. Comparison to the standard PDA shows a track loss reduction with the proposed method.

• 出版日期2018-2