信息支援条件下协同空战态势评估研究（英文）

Situation Assessment on Cooperative Air Combat with Information Support

针对现有空战态势评估方法表现形式不够直观、模型简单的问题,提出一种将威力场与遗传神经网络相结合的态势评估方法,并将其应用于信息支援条件下的协同空战态势评估。分别从攻击能力、探测能力、电子干扰能力、生存能力、通信能力、告警能力、协同能力以及决策能力等方面构建威力势模型。利用遗传算法优化BP神经网络,并将其应用于编队作战能力评估。最后利用具体算例进行仿真验证,结果表明该方法是正确可行的。相比于传统态势评估方法,该方法在信息支援条件下的超视距协同空战态势评估中具有全面性、直观性、准确性等优势。

Considering on the remaining problem in current situation assessment of air combat,such as lack of visualization and crude of the model,a situation method,which is consist of combat power field and neural networks,is proposed and applied in the cooperative air combat with information support.Optimized by genetic algorithms,the BP neural networks is applied in situation assessment on formation air combat ability. The method is verified by the simulation and the result shows the method in the paper has advantages of visualization,figurativeness and integrity compared with former situation assessment methods.