系统工程与电子技术(英文版)2024,Vol.35Issue(6) :1428-1440.DOI:10.23919/JSEE.2024.000096

Sea clutter suppression via cuttable encoder-decoder-augmentation network

ZANG Chuanfei WANG Yumiao WANG Xiang XU Congan CUI Guolong
系统工程与电子技术(英文版)2024,Vol.35Issue(6) :1428-1440.DOI:10.23919/JSEE.2024.000096

Sea clutter suppression via cuttable encoder-decoder-augmentation network

ZANG Chuanfei 1WANG Yumiao 1WANG Xiang 1XU Congan 2CUI Guolong1
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作者信息

  • 1. School of Communication Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
  • 2. Advanced Technology Research Institute,Beijing Institute of Technology,Jinan 250300,China;Naval Aviation University,Yantai 264000,China
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Abstract

This paper considers the problem of sea clutter sup-pression.We propose the cuttable encoder-decoder-augmenta-tion network(CEDAN)to improve clutter suppression perfor-mance by enriching the contrast information between the target and clutter.Specifically,the plug-and-play residual U-block(ResUblock)is proposed to augment the feature representation ability of the clutter suppression model.The CEDAN first extracts and fuses the multi-scale features using the encoder and the decoder composed of the ResUblocks.Then,the fused features are processed by the contrast information augmenta-tion module(CIAM)to enhance the diversity of target and clutter,resulting in encouraging sea clutter suppression results.In addi-tion,we propose the result-consistency loss to further improve the suppression performance.The result-consistency loss enables CEDAN to cut some blocks of decoder and CIAM to reduce the inference time without significantly degrading the suppression performance.Experimental results on measured and simulated data show that the CEDAN outperforms state-of-the-art sea clutter suppression methods in sea clutter suppres-sion performance and computation efficiency.

Key words

radar/sea clutter suppression/deep learning

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出版年

2024
系统工程与电子技术(英文版)
中国航天科工防御技术研究院 中国宇航学会 中国系统工程学会 中国系统仿真学会

系统工程与电子技术(英文版)

CSTPCD
影响因子:0.64
ISSN:1004-4132
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