无线电工程2025，Vol.55Issue(3)：484-492,9.DOI:10.3969/j.issn.1003-3106.2025.03.004
基于证据理论的可见光和红外融合检测算法
Fusion Detection Algorithm of Visible Light and Infrared Information Based on Evidence Theory
摘要
Abstract
UAVs are widely used for their high mobility and adaptability.However,target detection methods based on a single type of sensors cannot meet the target detection requirements of UAV in high-speed and complex motion scenarios.To address the problems above,a detection and fusion algorithm that integrates visible and infrared information is proposed,which mainly includes image detection based on deep learning,data association and heterogeneous information fusion.The innovation point is integrating data association fusion algorithm and using evidence theory to perform decision-level fusion of association results to complete candidate target recognition and detection.The proposed method is verified by some scenes of public dataset OTCBV and UAV aerial photography data.The experimental results show that the multi-source information fusion detection algorithm updates the detection accuracy rate of YOLO by combining various evidences and improves it to more than 0.9.关键词
无人机/目标检测/DS证据理论/信息融合Key words
UAV/target detection/DS evidence theory/information fusion分类
计算机与自动化引用本文复制引用
周策,赵秋博,王明杰,宗茂,刘龙..基于证据理论的可见光和红外融合检测算法[J].无线电工程,2025,55(3):484-492,9.基金项目
国家自然科学基金(62276204) （62276204）
陕西省自然科学基础研究计划(2022JM-336)National Natural Science Foundation of China(62276204) （2022JM-336）
Natural Science Basic Research Program of Shaanxi(2022JM-336) （2022JM-336）
