机动发射弹道导弹集群诸元快速规划

Aiming at the rapid planning of flight data of ballistic missile cluster under the condition of mobile launch, a rapid planning method of ballistic missile launch data is proposed by combining neural network prediction with least square optimization. Firstly, the flight strategy of the ballistic missile in the boost phase is analyzed and the appropriate launch data is selected. With the launch and landing point information as the inputs, the dual hidden layer data prediction network is designed. The trajectory data is obtained through the trajectory simulation, and the dataset is established to complete the network training. The iterative initial value of the launch data can be obtained by using the network. On this basis, in order to eliminate the influence of imbalance of sample data in the data set on the planning accuracy of launch data, the minimum deviation of range, cross range and elevation of the landing point is taken as the index function, and the accurate solution of launch data is obtained by iteration with the least square optimization method. Finally, the rapid mobile launch simulation of ballistic missile cluster is carried out in a typical launch scenario. The results show that this method can significantly improve the computing speed and accuracy compared with the traditional method, and can meet the rapid and accurate attack of ballistic missile cluster against the long distance and multiple targets under the given large range of maneuvering conditions.