电波科学学报2026，Vol.41Issue(1)：3-16,14.DOI:10.12265/j.cjors.2025068
面向雷达智能感知的语义电磁散射建模
Semantic electromagnetic scattering modeling for radar intelligent perception
摘要
Abstract
Radar image interpretation is one of the key technologies for promoting wide applications of radar satellites and supporting future unmanned intelligent platforms.Microwave vision,as a perceptual inverse problem for understanding the physical world through electromagnetic data,focuses on deriving semantic information from microwave radar images according to physics principles.Its forward problem involves"microwave graphics"that characterize the interaction mechanisms between electromagnetic waves and the physical world,aiming to develop electromagnetic scattering modeling suitable for perceptual inverse problems.This paper proposes a semantic electromagnetic scattering modeling framework for radar intelligent perception,which centers on target semantics and introduces diversity-oriented randomness modeling.This approach shifts the focus from pursuing one-to-one consistency of individual samples to ensuring distributional consistency across sample populations.This paper elaborates on the problem background,fundamental properties,and key tasks of semantic electromagnetic scattering modeling,presenting technical roadmaps at two levels:the primitive scatterer dictionary and the semantic representation tree.Finally,some relevant research progresses of the authors are briefly introduced.关键词
合成孔径雷达(SAR)/雷达智能感知/语义散射建模/微波视觉Key words
synthetic aperture radar(SAR)/radar intelligent perception/semantic scattering model/microwave vision分类
天文与地球科学引用本文复制引用
徐丰,张旭,岳子瑜,卫江涛..面向雷达智能感知的语义电磁散射建模[J].电波科学学报,2026,41(1):3-16,14.基金项目
国家重点研发计划工程科学与综合交叉重点专项(2024YFF0505503) （2024YFF0505503）
国家自然科学基金重点国际(地区)合作研究项目(W2411057)The National Key R&D Program of China—Key Special Project on Engineering Science and Multidisciplinary Integration(2024YFF0505503) （地区）
Key International(Regional)Joint Research Program of the National Natural Science Foundation of China(NSFC)(W2411057) （Regional）
