分布式模糊自动删除单元平均恒虚警检测  

Distributed Fuzzy Automatic Censoring Cell Averaging-Constant False Alarm Rate Detection

作　　者：郝程鹏[1] 张立军[1] 蔡龙[1] 侯朝焕[1] 

机构地区：[1]中国科学院声学研究所,北京100190

出　　处：《兵工学报》2010年第9期1274-1278,共5页Acta Armamentarii

基　　金：国家自然科学基金资助项目(60802072)

摘　　要：为提高多传感器分布式恒虚警(CFAR)检测的性能,基于模糊逻辑和自动删除单元平均(ACCA)算法提出一种新的多传感器分布式CFAR检测系统(分布式模糊ACCA).系统中每个模糊ACCA-CFAR检测器根据参考单元计算出映射到虚警空间的隶属函数值,然后传给融合中心,融合中心根据这些值采用模糊融合准则进行判决。仿真结果表明:分布式模糊ACCA-CFAR不但在均匀背景下具有较低的检测损失,而且在非均匀背景下具有更好的鲁棒性;同时模糊代数积融合比二元与融合和二元或融合提供更好的检测性能。该研究成果可应用于警戒雷达系统。In order to improve the performance of multiple-sensor distributed constant false alarm rate（CFAR）detection,a new distributed fuzzy ACCA-CFAR detection scheme based on fuzzy logic and automatic censoring cell averaging（ACCA）algorithm was proposed.In this scheme,each fuzzy ACCA-CFAR detector computes the membership function value mapping to the false alarm space from the samples of the reference cells and transmits it to the fusion center.The values are combined to derive a global decision with fuzzy fusion rules.The simulated results show that the distributed fuzzy ACCA-CFAR can provide low CFAR loss in homogeneous background and better robustness in the presence of interfering targets and clutter edge situation;furthermore fuzzy algebraic product operator provides better detection performance than binary ＇or＇ fusion and binary ＇and＇ fusion.This scheme can be applied advantageously to early warning radar system.

关 键 词：雷达工程 分布式恒虚警 自动删除单元平均 模糊逻辑 隶属函数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]