Phase trajectory entropy: A promising tool for passive diver detection

Zhang Hongwei, Wang Haiyan, Yao Haiyang, Dong Haitao, Shen Xiaohong

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Passive diver detection is really significant as it constitutes a potential real-time monitoring of serious underwater threats. Up to now, there is still a lack of an efficient approach to characterize the complexity and fickleness with non-parametric and non-information priors. To achieve an improvement, a phase trajectory entropy method is proposed that should be promising. A coarser-grained distribution is created during entropy counting. The value of phase trajectory entropy is demonstrated by simulation and applied to real recorded data. The results show that phase trajectory entropy method considerably outperforms narrowband energy detection and the bubble entropy method.

Original languageEnglish
Article number076003
JournalJASA Express Letters
Volume1
Issue number7
DOIs
StatePublished - 1 Jul 2021

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