Search Technology for Aircraft Debris Integrating Data Augmentation and Deep Learning Algorithm
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.
NETL
NSTL
万方数据
