融合数据仿真与深度学习算法的飞行器残骸搜寻技术  

Search Technology for Aircraft Debris Integrating Data Augmentation and Deep Learning Algorithm

作　　者：杨哲 崔颖函 郭灵犀 李嘉鑫 吴旭生 Yang Zhe;Cui Yinghan;Guo Lingxi;Li Jiaxin;Wu Xusheng(Science and Technology on Space Physics Laboratory,Beijing 100076,China)

机构地区：[1]空间物理重点实验室,北京100076

出　　处：《系统仿真学报》2024年第10期2238-2245,共8页Journal of System Simulation

摘　　要：飞行器残骸的可靠回收对于飞行试验数据的完整获取及型号后续的攻关研制具有重要意义。为保证飞行试验的安全性,飞行器试验的落区地点一般为无人区,且飞行器实际落点往往与理论落点有所偏差,残骸目标特性复杂、散布区域大,仅依靠人力完成对飞行器残骸的搜寻十分困难。针对飞行器落区残骸回收的难点问题,依托无人机平台搭载光学载荷的手段,开展融合数据仿真与深度学习算法的飞行器残骸搜寻技术研究,重点介绍了残骸搜寻的目标检测算法、数据仿真策略及应用效果。经实际测试,提出的智能搜寻方案效果良好,在多次任务中顺利完成飞行器残骸的快速定位,保障了飞行试验任务的圆满成功。The reliable recovery of aircraft debris is of great significance for the complete acquisition of flight test data and the subsequent research and development of models.To ensure the safety of flight tests,the landing area of aircraft experiments is generally an unmanned area,and the actual landing point of the aircraft often deviates from the theoretical landing point.The characteristics of the debris target are complex and the dispersion area is large,making it difficult to search for aircraft debris solely by manpower.Aiming at the difficult problem of aircraft debris recovery in the landing area,through on UAV platforms carrying optical payloads,the research on aircraft debris search technology which integrates data simulation and deep learning algorithms is carried out.The object detection algorithm,data simulation strategy,and application effects of debris search are introduced.Through practical testing,the proposed intelligent search scheme shows good performance,which successfully completes the rapid positioning of aircraft debris in many missions,and ensures the successful completion of flight test missions.

关 键 词：残骸搜寻 无人机 目标检测 深度学习 数据仿真 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]