Abstract：In the three-body game scenario, it is necessary to predict the trajectory of incoming targets to enhance the interception capabilities of defensive missiles. Limited by the transmission rate of data link, the update frequency of target information is low, and the trajectory prediction method based on the Kalman filter and trajectory fitting is not applicable. Therefore, this study presents a target trajectory prediction method capable of classification under low information support. Firstly, the trajectory database of incoming targets was established based on the detection ability of airborne radar, and then the classification neural network and trajectory prediction neural network were trained using the trajectory database. The type of the target was determined online according to the target information transmitted by the data link, and after that, the optimal estimation of the initial state of the incoming target was acquired by the least square method. Finally, the trajectory prediction was realized. Simulation results show that the proposed method can successfully achieve high-precision trajectory prediction under low information support condition.
陈万春, 袁文婕, 于琦, 刘小明, 徐增. 低信息条件下的机载拦截武器目标分类轨迹预报方法研究[J]. 空天防御, 2024, 7(4): 81-87.
CHEN Wanchun, YUAN Wenjie, YU Qi, LIU Xiaoming, XU Zeng. Research on Target Classification and Trajectory Prediction Method of Airborne Interceptor Weapons Under Low Information Condition. Air & Space Defense, 2024, 7(4): 81-87.
