摘要
基于不确定证据与不确定先验知识和谐的思想，利用模糊条件证据理论，给出一种融合模糊先验知识的新的雷达辐射源识别方法。首先，把雷达辐射源模糊观测数据表示为Dempster-Shafer（D—S）证据的随机集形式；然后，计算观测证据与模糊先验知识之间的和谐度；最后，利用模糊条件证据理论把需要融合的证据进行组合。这种方法可充分利用各种不同来源的信息，从而提高雷达识别的可靠性。
Based on the concept of the concordance existing between the ambiguous evidences and the ambiguous prior knowledge, and based on the fuzzy conditional Dempster-Shafer （D-S） evidence theory, a novel radar emitter recognition method was provided which reflected the influences of fuzzy prior knowledge First, the fuzzy measurements about radar emitter were changed into the form of fuzzy bodies of D-S evidences, and then, the fuzzy conditional D-S evidence theory was applied to combine these evidences, and calculate the concordance. This method can help us to increase the reliability of radar emitter recognition under complex battle circumstances
出处
《海军航空工程学院学报》
2009年第3期313-316,共4页
Journal of Naval Aeronautical and Astronautical University
基金
海军航空工程学院基础研究基金(08JCJJ004)
关键词
辐射源识别
随机模糊集
随机模糊条件事件
和谐
灰关联度
emitter recognition
random fuzzy sets
random fuzzy conditional event
concordance
gray correlation grade
