Weak Target Detection Within Sea Clutter Based on EMD Fractal Feature

Yifei Fan, Xinbao Wang, Yanyun Gong, Zheng Guang Li

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

1 Scopus citations

Abstract

In order to improve the target detection performance within sea clutter under low signal-to-clutter ratio (SCR), this paper focuses on the empirical mode decomposition (EMD) fractal property of sea clutter and its application on weak target detection. Firstly, the radar signals are reconstructed by EMD algorithm to suppress the impact of noise. Then the autoregressive (AR) spectrum fractal property of the reconstructed signal is analyzed in detail and the EMD-AR Hurst exponent is extracted for target detection. Finally, from analysis of the real radar sea clutter datasets, the results demonstrate that the proposed method increase the target detection probability than the traditional constant false alarm rate (CFAR) method and the existing fractal-based method under a low SCR condition.

Original languageEnglish
Title of host publication2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789463968096
DOIs
StatePublished - 2023
Event35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023 - Sapporo, Japan
Duration: 19 Aug 202326 Aug 2023

Publication series

Name2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023

Conference

Conference35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
Country/TerritoryJapan
CitySapporo
Period19/08/2326/08/23

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