The recognition of flight maneuvering is primarily utilized for assessing pilot training quality， aiding decision-making in aerial combat， and other related scenarios. This study focuses on realizing flight maneuver recognition through the utilization of the bag of patterns （BoP） algorithm， which has been enhanced to address deficiencies in multi-dimensional time series scenarios. The improved algorithm extracts features from flight attitude data and analyze flight maneuver recognition. Simulation results demonstrate that the enhanced BoP algorithm enhances the accuracy and confidence of flight maneuver recognition， while effectively characterizing specific flight maneuvers through extracted parameter features.

To deal with the difficulties in physical damage information extraction and functional damage assessment in damage assessment of phased array antenna,an intelligent damage assessment method is explored by using computer vision and phased array antenna simulation technology.On the basis of space reconnaissance images,the position of damaged array elements is extracted by computer vision technology,and the physical damage results are obtained.According to the position information of the array elements,the antenna model is built in the Matlab environment,and the changes of detection distance and anti-jamming before and after the attack are simulated and compared to obtain the functional damage.The simulation results show that the proposed method can better extract the physical damage information and build the mapping relationship between physical damage and functional damage through software simulation.The relevant research results provide a new method and idea for intelligent and rapid phased array antenna damage assessment.