舰船电子工程2026，Vol.46Issue(4)：39-46,8.DOI:10.3969/j.issn.1672-9730.2026.04.008
基于跨尺度协同感知的无人机目标检测算法
Unmanned Aerial Vehicle Target Detection Algorithm Based on Cross-scale Collaborative Perception
摘要
Abstract
To address the challenges of dense distribution of small targets and significant multi-scale variations in unmanned aerial vehicle(UAV)aerial images,this paper proposes a Cross-Scale Collaborative Perception YOLO(CSCP-YOLO)object de-tection algorithm.Firstly,a cross-scale adaptive perception module is designed,which achieves adaptive perception of targets at different scales through the collaborative fusion of receptive field attention mechanism and coordinate attention mechanism.Second-ly,a cross-scale collaborative feature fusion network is constructed,which establishes a four-level cross-scale perception pyramid from P2 to P5 through sequential collaborative fusion and feature collaborative enhancement.Finally,a cross-scale collaborative perception detection head is proposed,which adopts a cross-scale parameter collaborative sharing strategy to achieve unified detec-tion of multi-scale targets.Experimental results on the VisDrone2019 dataset show that CSCP-YOLO achieves 6.9%improvement in mAP@0.5 and 4.3%improvement in mAP@0.5:0.95 compared to the baseline YOLOv11n algorithm,while reducing the parame-ter count by 5.5%.Generalization experiments on the DOTA v1.0 dataset further validate the cross-scale perception capability of the algorithm.关键词
目标检测/无人机航拍图像/跨尺度协同感知/深度学习/多尺度特征融合Key words
object detection/UAV aerial images/cross-scale collaborative perception/deep learning/multi-scale feature fusion分类
信息技术与安全科学引用本文复制引用
向宇,刘丽,李晓举,王睿龙,王海燕,许思寒..基于跨尺度协同感知的无人机目标检测算法[J].舰船电子工程,2026,46(4):39-46,8.基金项目
国家自然科学基金项目(编号:62302463) （编号:62302463）
河南省科技攻关项目(编号:252102211079) （编号:252102211079）
河南省高等教育教学改革研究与实践项目(研究生类)(编号:2023SJGLX329Y) （研究生类）
郑州航院研究生教育创新计划基金项目(编号:2025CX116)资助. （编号:2025CX116）
