基于灰度量空间的辐射源识别方法  

A GMS-Based Emission Source Identification Method

作　　者：周宪英[1] 张怀巍[2] 关欣[2] 

机构地区：[1]92941部队96分队 [2]海军航空工程学院信息融合技术研究所

出　　处：《计算机与数字工程》2013年第2期191-195,共5页Computer & Digital Engineering

基　　金：国家自然科学基金重点项目(编号:61032001);新世纪优秀人才支持计划(编号:NCET-11-0827)资助

摘　　要：针对复杂电磁环境中电子侦察传感器获得的辐射源信息可能同时含有一般标量数据和区间型数据的情况,提出了灰度量空间的概念,并基于该空间给出了对标量、区间数混合的行为序列的灰关联分析方法。该方法将后验加权灰关联度作为单个传感器的识别证据,D-S证据理论融合结果作为多传感器系统的最终判决依据。大量的仿真结果表明,算法具有较高的目标识别率,对差环境亦具有更好的稳定性能。Aiming at the probable scene that both interval-value and common scalar datas exist in radiation source information,acquired by electronic reconnaissance sensor in complex electromagnetic circumstance,a conception,Gray Metric Space（GMS）,was proposed.Based on this space,an gray correlation method for behavior sequences with scalar numbers and interval-value numbers was put forward.And in this paper,a posterior weighted gray correlation degree was selected as the evidence for a single sensor,while the fusion of different evidences by D-S combination rule as the final evidence for a multi-sensor system.Results from numbers of simulations show that this algorithm has higher objective recognition rate and better performance under bad circumstances.

关 键 词：辐射源识别 灰域度量空间 灰关联分析 D-S证据理论 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]