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所属单位：BUPT

教研室：ICC

发表刊物：IEEE Sesnsors Journal

关键字：Graph Attention Network; heterogeneous radar network; object recognition

摘要：Radar target recognition (RTR), as a key technique of intelligent radar systems, has been widely investigated. Accurate RTR at low signal-to-noise ratios (SNRs) still remains an open challenge. Considering that most existing methods are based on a single radar or the homogeneous radar network, we extend RTR to the heterogeneous radar network in order to improve the robustness of RTR which uses the RCS signals at low SNRs by further exploiting the frequency domain information. In this paper, a Semantic Feature Enhanced Graph ATtention Network (SFE-GAT), is proposed, which extracts semantic feat

论文类型：期刊论文

第一作者：Han Meng

合写作者：Wei Xiang,Xu Pang

通讯作者：Yuexing Peng,Wenbo Wang

论文编号：DOI: 10.1109/JSEN.2023.3250708

学科门类：工学

一级学科：信息与通信工程*

文献类型：J

卷号：23

期号：7

页面范围：1-8

ISSN号：1530-437X

是否译文：否

发表时间：2023-03-06

收录刊物：SCI

发布期刊链接：https://ieeexplore.ieee.org/document/10061371