基于VD.AiNet聚类算法的空袭目标类型识别

Type Recognition of Air-Attack Target Based on VD-AiNet Cluster Algorithm

针对防空反导作战中空袭目标类型识别问题,在分析空袭目标的主要类型、识别指标及其识别原则的基础上,将人工免疫算法中矢量距人工免疫网络聚类算法应用于抗体样本训练模块,并建立了抗体训练和目标识别的并行决策模型。最后进行了算例验证,结果表明了算法和模型的可行性和有效性。

To solve the problem of recognizing aerial defense and antimissile target type, based on the analysis of the primary air-attack target types, important useful factors and primary recognition principles, the vector distance primary artificial immune network cluster algorithm of artificial immune algo-rithm is used in the model of antibody swatch training. Furthermore, the side-by-side decision making model of antibody training and target recognition are established. Finally, the algorithm and model is validated with examples, proving the utility and effectiveness of the algorithm and model.