摘要
基于观测证据与先验信息和谐的思想,利用条件证据理论,提出了一种融合先验信息的雷达辐射源识别方法.首先将雷达辐射源观测数据通过灰关联分析表示为D-S数据的随机集形式,然后计算观测证据与先验知识之间的和谐度,最后利用条件证据理论将需要融合的证据进行组合.该方法可在复杂战场环境下充分利用不同来源的信息,提高雷达识别的可靠性.
Based on the concept of the concordance existing between the measurement evidences and the prior knowledge, and on the conditioning Dempster-Shafer evidence theory, this paper provides a novel radar emitter recognition approach which reflects the influences of prior knowledge. The first step for this approach is to change the measurements on the radar emitter into the form of bodies of D-S evidence by the application of gray correlation analysis. Furthermore, we apply the conditioning D-S evidence theory 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
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2006年第5期833-837,共5页
Journal of Xidian University
基金
国家自然科学基金资助(60172033)
全国优秀博士论文作者专项基金(200036200237)
关键词
随机集
随机条件事件
灰关联度
辐射源识别
random set
random conditional event
gray correlation grade
emitter recognition
