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基于多路径特征融合的非视距目标识别方法

曾小路 杨怡菲 赵涵 钟世超 杨小鹏

信号处理2026,Vol.42Issue(3):357-370,14.
信号处理2026,Vol.42Issue(3):357-370,14.DOI:10.12466/xhcl.2026.03.006

基于多路径特征融合的非视距目标识别方法

Non-Line-of-Sight Target Recognition Method Based on Multi-Scale Feature Fusion

曾小路 1杨怡菲 1赵涵 1钟世超 1杨小鹏1

作者信息

  • 1. 北京理工大学信息与电子学院,北京 100081||北京理工大学长三角研究院(嘉兴),浙江 嘉兴 314000
  • 折叠

摘要

Abstract

The accurate classification of targets concealed in non-line-of-sight(NLOS)regions,such as armed person-nel or unmanned aerial vehicles behind building corners,holds significant value for modern urban warfare and intelli-gent driving systems.However,the complexity of electromagnetic wave propagation in NLOS scenarios often intro-duces multipath interference,blurred path boundaries,and signal distortion in echoes,thereby undermining the reliabil-ity of traditional classification methods that rely on geometric modeling or handcrafted features.To address these chal-lenges,this study proposes a multipath feature fusion network for NLOS target classification.First,the echo characteris-tics of four representative target types were analyzed:pedestrians,soldiers carrying anti-tank weapons,quadrotor drones,and tank models.Given the variability in multipath returns and boundary blurring,an adaptive multi-scale fea-ture extraction module was designed.Specifically,small-scale convolutional kernels were employed to capture fine-grained,high-amplitude features in single-path echoes,whereas large-scale kernels were used to extract global struc-tural information related to multiple propagation paths.Additionally,an attention mechanism was incorporated to effec-tively fuse salient multipath features with local scattering information,thereby enhancing classification accuracy under NLOS conditions.Finally,real-world measurements collected with a multipath radar sensing system were used for vali-dation.The experimental results demonstrate that the proposed network achieved a target classification accuracy of 99.6%.Comparative experiments confirmed the effectiveness and robustness of the proposed method.

关键词

非视距目标识别/卷积神经网络/多尺度卷积核

Key words

non-line-of-sight target recognition/convolutional neural network/multi-scale convolution

分类

信息技术与安全科学

引用本文复制引用

曾小路,杨怡菲,赵涵,钟世超,杨小鹏..基于多路径特征融合的非视距目标识别方法[J].信号处理,2026,42(3):357-370,14.

基金项目

国家自然科学基金(62301042) (62301042)

科技创新领军人才(3050013532502) The National Natural Science Foundation of China(62301042) (3050013532502)

National leading talent Project(3050013532502) (3050013532502)

信号处理

1003-0530

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