液晶与显示2026，Vol.41Issue(7)：1023-1038,16.DOI:10.37188/CJLCD.2026-0090
YOLO26-DeepSpace:一种面向深空弱小目标的多尺度多目标检测跟踪网络
YOLO26-DeepSpace:a multi-scale and multi-target detection and tracking network for dim and small targets in deep space
摘要
Abstract
For space early warning and space target surveillance systems,aiming to effectively detect various space debris and other small-size,weak-signal celestial targets,this paper proposes a target detection and tracking algorithm based on improved YOLO26 to address the challenges in deep space environments such as noise interference,faint target features and discontinuous trajectories.Firstly,an image sub-region self-perception enhancement module is deployed to enhance the visual clarity of dim and dark targets via local contrast optimization and edge preservation mechanism.Secondly,the YOLO26 detection network is lightweighted,and an improved multi-scale attention module GCEMA is introduced to strengthen the detection capability for dim and small targets.Finally,combined with the OCSort tracking algorithm and the appearance re-identification model CosmicReID,multi-target cataloging and stable tracking are realized.Experimental results show that compared with the original YOLO26 network and OCSort algorithm,the improved network has fewer parameters and faster inference speed,with the detection speed increased by 11.9%;the tracking accuracy of the integrated system is improved by 6.2%,and the frequency of target identity switching is reduced by 48.5%.The proposed method meets the requirements on detection accuracy and tracking accuracy of automatic tracking and measurement systems.关键词
多目标跟踪/图像处理/目标检测/数据关联Key words
multi-target tracking/image processing/object detection/data association分类
信息技术与安全科学引用本文复制引用
赵妍妍,曹玥..YOLO26-DeepSpace:一种面向深空弱小目标的多尺度多目标检测跟踪网络[J].液晶与显示,2026,41(7):1023-1038,16.基金项目
吉林省科技发展计划(No.20240206004YY)Supported by Jilin Province Science and Technology Development Plan(No.20240206004YY) （No.20240206004YY）
