协同多目标攻击空战决策及其神经网络实现

 提出了一种超视距多目标空战决策方法——协同优先权算法。它能给出多机协同攻击多目标的目标配对。然后对２∶４空战，用３层Ｂ－Ｐ网络实现该算法，并用ＳＯＦＭ网络实现对目标的攻击排序。因它们具有很强的适应、容错能力和实时性，故这种实现将有助于复杂动态环境下飞行员的空战决策，以及提高航空武器系统的作战效能。仿真结果证实了上述思想的正确性。

AIR COMBAT DECISION OF COOPERATIVE MULTI TARGET ATTACK AND ITS NEURAL NET REALIZATION

First, a decision method of Beyond Visual Range(BVR) multi target air combat cooperative prioritization algorithm is presented, by which the target distribution of cooperatively attacking multiple targets by multiple fighters can be given. Then, for 2 via 4 air combat, the algorithm is realized by three layers of B P neural network, and the object attacking sequence is realized by a Self Organ Feature Mapping(SOFM) one. In accordance with the concrete features of the learning algorithm of them, appropriate sample space, training and testing methods are designed. Thus, favorable results have been obtained when they are trained and tested. This research shows that it is easy, accurate and fast to realize the object attacking sequence of air combat by means of SOFM neural network. Because they have strong capability of environment adaptation, error tolerance and real time characteristic, the realization must be helpful to the pilot’s air combat decision in a complicated and dynamic environment, and can enhance the fighting effectiveness of the aeronautical weapon system.