空天防御2026，Vol.9Issue(1)：73-79,7.
基于窗口注意力机制的可见光-SAR跨模态目标匹配方法
A Cross-Modal Target Matching Method for Optical Image and SAR Images Based on Window Attention Mechanism
摘要
Abstract
This study addresses the issues of low efficiency and accuracy in target matching within remote sensing ship tracking scenarios,which are attributed to significant modal differences between optical images and synthetic aperture radar(SAR)images,as well as the inadequacy of cross-modal matching technology.In response,a novel optical-SAR cross-modal target matching method employing a window attention mechanism is proposed.The method designed a cross-modal dual-branch embedding module to process the two image types separately and extracted modality-agnostic features via a hierarchical window attention mechanism.It fused the modal information embedding and ship-size embedding to supplement the semantic and physical attribute information of ships and to enhance the learning of cross-modal-aligned features.Experimental results show that the proposed method achieves an overall mean Average Precision(mAP)of 46.0%,Top-1(R1)matching accuracy of 60.8%,Top-5(R5)matching accuracy of 74.4%,and Top-10(R10)matching accuracy of 79.5%on the HOSS dataset.Compared with the state-of-the-art TransOSS model,R5 and R10 achieve improvements of 3.4%and 1.1%respectively.The key matching indicators in both the optical-to-SAR and SAR-to-optical directions are superior to those of the current optimal model.The research indicates that the proposed method outperforms the SOTA(state-of-the-art)model and provides technical support for continuous ship tracking across scenarios such as maritime search and rescue and shipping supervision.关键词
可见光-合成孔径雷达(SAR)/窗口注意力/跨模态目标匹配/遥感图像处理/船舶跟踪Key words
optical-synthetic aperture radar(SAR)/window attention/cross-modal target matching/remote sensing image processing/ship tracking分类
航空航天引用本文复制引用
杨明慧,韦亚利,卢俊言,李昕海..基于窗口注意力机制的可见光-SAR跨模态目标匹配方法[J].空天防御,2026,9(1):73-79,7.基金项目
浙江省自然科学基金资助项目(LQ23F010025) （LQ23F010025）
中国航天科技集团有限公司上海航天科技创新基金资助项目(SAST2022-001) （SAST2022-001）
