基于贝叶斯网络的目标融合识别方法研究

利用贝叶斯网络模型进行目标融合识别是近年来的一个研究热点。以电子战环境中的数据融合为背景，提出了一种以朴素贝叶斯分类器和扩展的朴素贝叶斯分类器为基本结构的目标融合识别模型，采用同质传感器数据优先融合原则对雷达侦察、通信侦察和红外成像侦察数据进行融合。仿真实验表明，该模型可以有效地提高识别系统的准确率、可靠性和稳健性。

Information Fusion with Bayesian Networks for Target Recognition

Information fusion with Bayesian Networks for target recognition has become a focus in recent years. A probabilistic model of information fusion for target recognition under the background of information fusion in Electronic Warfare was introduced, in which the information from radar reconnaissance, communication reconnaissance and infrared photographic reconnaissance were integrated under the principle of homogeneity data first, and the basic structure of Naive Bayes classifier and Augmented Naive Bayes classifier. The experiment result shows that the model could make the recognition more accurate, more reliable and more robust.