Target assignment and sorting for multi-target attack in Multi-aircraft coordinated based on RBF

Fu Li, Wang Qi, Xu Jin, Zhou Yuandong, Zhu Kun
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引用次数: 3

Abstract

In this paper, we make the UAV air combat as the background. Based on air combat situation and target's air combat ability, the threat evaluation model of UAV air combat is established, then it uses RBF neural network to identify complex nonlinear relation between the types of threats to get the overall threat situation. In the course of air combat, we get the threat situation index of air combat, and then get the target threat matrix through RBF neural network. Finally, it uses the matrix method to get the result of target assignment and sorting. The experimental results show that RBF neural network can successfully approximate the weights of all the types of threats.
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基于RBF的多机协同多目标攻击目标分配与排序
本文以无人机空战为研究背景。基于空战态势和目标空战能力,建立了无人机空战威胁评估模型,利用RBF神经网络识别各种威胁类型之间的复杂非线性关系,得到整体威胁态势。在空战过程中,首先得到空战威胁态势指标,然后通过RBF神经网络得到目标威胁矩阵。最后,利用矩阵法得到目标分配和排序结果。实验结果表明,RBF神经网络可以成功地逼近所有类型威胁的权值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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