基于逆云模型的雷达辐射源识别方法  

Novel Method for Emitter Recognition Based on Backward Cloud Model

作　　者：关欣[1,2] 郭强[1] 张政超[3] 翟鸿君[4] 何友[1] 

机构地区：[1]海军航空工程学院信息融合技术研究所 [2]国防科学技术大学电子科学与工程学院 [3]中国人民解放军63880部队 [4]海军航空工程学院基础部

出　　处：《电子科技大学学报》2012年第5期663-667,677,共6页Journal of University of Electronic Science and Technology of China

基　　金：国家自然科学基金(60572161);新世纪优秀人才支持计划(NCET-11-0872)

摘　　要：针对由于噪声环境造成的雷达辐射源不能正确识别的问题,提出了一种新的基于逆云模型的雷达辐射源识别方法。该方法首先构建了更符合实际的含有噪声数据的雷达辐射源数据库,利用逆云模型求出数据库中雷达辐射源各属性的云数字特征,给出了基于属性相似度的识别权重确定方法,并构建了基于云模型和属性相似度的雷达辐射源分类器。仿真实验证明,该方法可以更好地处理由于噪声环境引起的随机性和模糊性,能在恶劣噪声环境下有效地进行雷达辐射源识别。To deal with the problem of radar emitter recognition caused by noise environment, this paper presents a new method for emitter recognition based on backward cloud model and attribute similarity. In this method, a radar emitter database including noise data according with the reality is first constructed, the cloud numerical characteristic is then calculated based on backward cloud model. After that, the method for determining recognition weight of coefficients and a new classification implement based on backward cloud model and attribute similarity are proposed. Simulation results show that the proposed method can deal with the randomness and vagueness caused by noise environment much better and can conduct emitter recognition effectively in the adverse noise environment.

关 键 词：属性相似度 逆云模型 雷达辐射源 信号识别 

分 类 号：TN95[电子电信—信号与信息处理]