Small Target Detection in Sea Clutter by Time-Frequency Tri-Feature based SVM Detector

Dan Fang, Jia Su, Haojiano Li, Xiang Zhang, Yifei Fan, Tao Li

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

4 Scopus citations

Abstract

A SVM detector utilizing three time-frequency features is proposed to discriminate floating small targets in sea clutter environment. The detector consists of three stages. Firstly, transform radar echoes into time-frequency domain. Then, three features, i.e. kurtosis, skewness and concentration, are extracted in the time-frequency domain. Finally, two-class support vector machine (SVM) detector is used to find floating small target under sea clutter background. The result of experiments using real datasets under different circumstances verifies the performance of our proposed method.

Original languageEnglish
Title of host publicationICEICT 2020 - IEEE 3rd International Conference on Electronic Information and Communication Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages545-548
Number of pages4
ISBN (Electronic)9781728190457
DOIs
StatePublished - 13 Nov 2020
Event3rd IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2020 - Shenzhen, China
Duration: 13 Nov 202015 Nov 2020

Publication series

NameICEICT 2020 - IEEE 3rd International Conference on Electronic Information and Communication Technology

Conference

Conference3rd IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2020
Country/TerritoryChina
CityShenzhen
Period13/11/2015/11/20

Keywords

  • feature extraction
  • sea clutter
  • support vector machine
  • target detection

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