Track‐Before‐Detect Techniques
Samuel J. Davey, Mark G. Rutten, Neil J. Gordon · 2014
This chapter presents a review of many of the recent algorithms for track-before-detect (TBD) and assesses their performance. It presents an outline of the historical context of TBD and summarizes the key contributions to the field. It also motivates the study of TBD with an example where conventional tracking fails. The chapter defines models for targets and the measurements that are common among the alternative algorithms. It reviews a number of TBD algorithms: Baum Welch; Viterbi; the particle filter; maximum likelihood (ML) PDA; and histogram probabilistic multi-hypothesistracking (H-PMHT). The chapter presents an example application of TBD within a maritime surveillance context and the chapter concludes by identifying unsolved problems and future research areas for TBD.