基于霍夫曼树和逆云模型的雷达拖引干扰识别  

Identification of Radar Pull-off Jamming Based on Huffman Tree and Backward Cloud Model

作　　者：李芳[1] 熊英[1] 唐斌[1] 

机构地区：[1]电子科技大学电子工程学院,成都611731

出　　处：《数据采集与处理》2013年第4期497-501,共5页Journal of Data Acquisition and Processing

基　　金：装备预研基金(9140A07030713DZ02101)资助项目

摘　　要：针对噪声环境中雷达干扰正确识别率较低的问题,提出了一种新的基于霍夫曼树和逆云模型联合的雷达欺骗干扰识别方法。该方法首先利用干扰数据库,提取有效的识别特征参数库,然后基于霍夫曼树建立识别模型。在每个节点,利用基于逆云模型的隶属度分类,实现待测干扰的识别。仿真结果表明,与传统的干扰识别方法相比,该识别方法能很好地应对雷达干扰的随机性和模糊性,能在干扰参数数值区间有重叠时有效识别雷达干扰。A new method is presented to improve the identification rate of radar jamming for the identification of radar pull-off jamming based on Huffman tree and backward cloud model. Firstly, a parameter library is built according to the jamming library, then an identification model based on Huffman tree can be established. Finally the degree of membership is used to i- dentify jamming on each node of the tree. Compared with traditional method, the presented method deals well with the randomness and fuzziness of jamming caused by noise, and identi- fies jamming effectively when parameters overlap partially.

关 键 词：雷达拖引干扰识别 参数融合 霍夫曼树 逆云模型 

分 类 号：TN97[电子电信—信号与信息处理]