Noise-Robust HRRP Target Recognition Based on Residual Scattering Network

被引：0

作者：

Huang, Pengjun ^{[1
]}

Li, Shuai ^{[1
]}

Zheng, Muhai ^{[1
]}

Xie, Jingyang ^{[1
]}

Tian, Biao ^{[1
]}

Xu, Shiyou ^{[1
]}

机构：

[1] Sun Yat Sen Univ Shenzhen Campus, Sch Elect & Commun Engn, Shenzhen, Peoples R China

来源：

2024 9TH INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING, ICSIP | 2024年

基金：

中国国家自然科学基金;

关键词：

high-resolution range profile; scattering network; noise-robust feature extraction; radar target recognition;

D O I：

10.1109/ICSIP61881.2024.10671484

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Extracting noise-robust features is a key issue for high-resolution range profile (HRRP) target recognition. In order to enhance the recognition performance under low signal-to-noise ratio (SNR), a novel recognition method based on scattering network is proposed in this paper. Specifically, the initial scattering network is enhanced by the incorporation of squared modulus and residual connection, making it more suitable for HRRP. And it is cascaded with ResNet to further extract information and complete the recognition. Experimental results on two different datasets demonstrate the effectiveness and robustness of the proposed method.

引用

页码：37 / 41

页数：5

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