H-PMHT track-before-detect processing with DP-based track initiation and termination

Xuwang Zhang, Jinping Sun, Yuxi Zhang, Songtao Lu, Chao Liu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1118-1125
Number of pages8
JournalIET Signal Processing
Volume10
Issue number9
DOIs
StatePublished - Dec 1 2016

Bibliographical note

Funding Information:
The authors thank the Council for Scientific and Industrial Research (CSIR) in South Africa for providing the real data. This work was supported in part by the National Natural Science Foundation of China (61471019).

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