Open AccessH‐PMHT track‐before‐detect processing with DP‐based track initiation and termination
Author(s) -
Zhang Xuwang,
Sun Jinping,
Zhang Yuxi,
Lu Songtao,
Liu Chao
Publication year - 2016
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
ISSN - 1751-9683
DOI - 10.1049/iet-spr.2016.0208
Subject(s) - probabilistic logic , computer science , track (disk drive) , artificial intelligence , histogram , sort , computer vision , tracking (education) , false alarm , constant false alarm rate , track before detect , algorithm , image (mathematics) , kalman filter , particle filter , psychology , pedagogy , information retrieval , operating system
Histogram probabilistic multi‐hypothesis tracker (H‐PMHT), based on probabilistic multi‐hypothesis tracker, is a track‐before‐detect processing approach to detect dim targets. For the problem that H‐PMHT cannot initiate new tracks and terminate tracks of disappeared targets, the authors propose a new dynamic programming (DP)‐based H‐PMHT algorithm, which can locate new targets by dealing with a few frames of sensor images and confirm disappeared targets according to their energy accumulation values along the existing tracks. With this sort of track initiation and termination mechanism, H‐PMHT can be directly applied to realistic environments. Simulation results show that the DP‐based H‐PMHT algorithm can rapidly locate new targets and initiate tracks with a low false alarm rate, and quickly terminate tracks of disappeared targets with a low false termination probability.