Target Detection Method Based on Amplitude Statistical Entropy of Sea Clutter Model

Yifei Fan, Duo Chen, Shichao Chen, Mingliang Tao, Jia Su, Ling Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Maritime target detection is one of the most complicated problems in the radar signal processing field. Since traditional constant false alarm rate detection methods rely on the clutter distribution model, the mismatch of the sea clutter model leads to a decrease in the target detection performance. In this paper, the amplitude statistical entropy (ASE) of sea clutter sequence is extracted as a feature to describe the degree of aggregation of the sea clutter amplitude statistical histogram. Then a novel target detection algorithm based on ASE is proposed, which is not affected by the degree of the model matching between sea clutter datasets and statistical model. Finally, the experiment result based on the Canadian IPIX radar datasets confirms the effectiveness of this method.

Original languageEnglish
Title of host publicationIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages879-882
Number of pages4
ISBN (Electronic)9781665427920
DOIs
StatePublished - 2022
Event2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 - Kuala Lumpur, Malaysia
Duration: 17 Jul 202222 Jul 2022

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2022-July

Conference

Conference2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Country/TerritoryMalaysia
CityKuala Lumpur
Period17/07/2222/07/22

Keywords

  • entropy
  • Sea clutter
  • target detection

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