摘要
面对传统试飞模式改革大背景下“数智赋能试飞”中测试智能自动化能力构建愿景,针对近场道面段试飞科目对目标关键运动过程的高清影像视频记录需求,提出一种基于陆基云台的试飞目标定位跟踪方法。基于GPS/北斗动差分计算模型实时计算目标相对方位信息,引导云台转动并调整高清相机焦距,完成目标视场的自动捕获;之后采用融合全局注意力机制、Dynamic Head结构与Wise IoU损失函数的改进YOLOv5s算法,实现目标的实时检测与识别;最后结合中值流跟踪器、卡尔曼滤波与IoU阈值检测策略,完成目标的持续稳定跟踪。实验结果表明,该方法的全类平均检测正确率可达76.3%,处理帧率可达20 fps,能够有效支撑实际实际试飞工程应用需求。
In light of the reform of the traditional flight test mode,there is a proposal to construct the intelligent automation capability in the“Digital empowerment flight test”.To address the need for high-definition video recording of the target's key motion process in the near-field runway segment flight test,a target positioning and tracking method based on the ground-based PTZ.This method calculates the relative azimuth information of the target in real time using the GPS/Beidou differential calculation model.Based on this information,the PTZ is guided to rotate and adjust the focal length of the high-definition camera,enabling automatic capture of the target's field of view.Real-time detection and recognition of the target are then carried out using the YOLOv5s object detection algorithm,which has been improved with global attention mechanism,Dynamic head,and Wise IoU.By incorporating techniques such as median flow,Kalman filtering,and IoU threshold detection,long-term real-time tracking of the target is achieved.The experimental results demonstrate that the proposed method achieves a mean average precision of 76.3%for all categories,with a processing frame rate of 20 fps.This performance effectively supports the requirements of practical flight test engineering applications.
作者
马晓东
高帅华
张吉璇
Ma Xiaodong;Gao Shuaihua;Zhang Jixuan(Chinese Flight Test Establishment,Xi'an 710089,China)
出处
《电子测量技术》
北大核心
2025年第20期17-25,共9页
Electronic Measurement Technology
基金
国家自然科学基金(5212780114)项目资助。
