摘要
空中对来袭目标的威胁评估是指挥控制的重要环节,主要内容是综合雷达探测信息与相关情报对来袭目标的威胁度进行评估。评估的结果为后续的目标火力分配和打击提供重要参考。目前评估的难点技术在于如何有效的处理来袭目标的各种定量与定性信息,如何对获得情报的不确定性信息进行分析和处理。针对传统对目标信息处理方法的单一和不足,提出一种并行化处理的新方法。利用人工神经网络的强泛化能力处理目标的定量信息得到目标的动态威胁值,利用贝叶斯网络的强推理能力处理不确定性的定性指标得到静态威胁值,最后通过线性加权两种威胁值得到目标的综合威胁值。结合实例分析和Matlab、Genie软件仿真对10批目标的综合威胁值进行预测,仿真结果表明:得到的综合威胁值较传统的评估方法相比可信度更高。
Air targets threat assessment is an important part of command and control, the main content is to evalu- ate threat degree of air targets by integrating radar detecting information and other intelligence information. The result of evaluation provides important reference for the following fire distribution and blow. Recently, the technical difficul- ties of assessment are how to deal with quantitative and qualitative information effectively, and how to analyze and process uncertain information. Aiming at the single and the insufficiency of traditional processing method, a new par- allel processing method is put forward. The strong generalization ability of Back - Propagation is used to map quanti- tative indicators in order to get the dynamic threat value, at the same time, the strong reason ability of Bayesian net- work is used to analyze qualitative indicators to acquire the static threat value. Finally, the comprehensive threat value is got by linear weighting the two kinds of threat values. Through the case analysis and the prediction of ten batches of target, combined with the simulation in the Matlab and Genie software, the method is proved to be effective. Simu- lation result shows that the comprehensive threat value is more credible than which got by traditional method.
出处
《计算机仿真》
北大核心
2017年第8期54-58,共5页
Computer Simulation
基金
国家自然科学基金(61472441)
关键词
威胁评估
反向神经网络
贝叶斯网络
Threat assessment(TA)
Back - propagation network
Bayesian network