基于自动筛选技术的分布式CFAR检测算法  

Distributed adaptive CFAR detection based on automatic censoring technique

作　　者：刘盼芝[1] 韩崇昭[1] 

机构地区：[1]西安交通大学电信学院综合自动化所,陕西西安710049

出　　处：《系统工程与电子技术》2008年第6期1009-1014,共6页Systems Engineering and Electronics

基　　金：国家重点基础研究发展规划"973"项目资助课题(2001CB309403)

摘　　要：针对多传感器分布式恒虚警率(CFAR)检测技术在杂波环境下的应用,基于广义有序统计(OS)和自动筛选技术,提出了一种新的分布式多传感器目标检测算法。首先利用广义有序统计(OS)恒虚警算法来得到各传感器的杂波/噪声电平估计,然后将检测单元电平与估计得到的杂波/噪声电平比较,得到各传感器的局部判决。采用"OR"或者"AND"融合准则在融合中心形成全局判决,得到有无目标的判决。多目标引起的非均匀背景中,采用了自动筛选技术,使得干扰目标进入后沿滑窗的机会变小,对于干扰目标有较好的鲁棒性。在假定目标服从Swerling II起伏的情况下,导出了相应的检测概率与虚警概率闭式解。最后,给出了多种检测器数值和图表分析的比较结果,表明了该方法的有效性和优越性。To study the applied background of CFAR（constant false alarm ratio） processor in mult-distribution clutter, this paper presents a new distributed CFAR detector based on automatic censoring technique. In the scheme, every local decision of individual detector, resulting from the comparison between its sample level and the generalized order statistic （GOS） of its reference samples, takes the value zero or one. Then, the fusion center makes the final decision utilizing the total local decisions. which are transmitted from each GOS-CFAR. The overall decision, which is zero or one, is obtained at the data fusion center based on or ＂k/N＂ fusion rule. The result shows that for the nonhomogeneous background caused by multiple interfering targets, particularly in multiple target situations, it exhibits good robustness for MOS （maximum order statistic）, mOS（minimum order statistic）, and OSOR（order statistic ＂OR＂）, ORAND（order statistic ＂OS＂） in distributed sensor net-works. Under Swerling 2 assumption, the analytic expressions of the detection probability and the false alarm probability are derived.

关 键 词：分布式融合检测 自动筛选技术 检测概率 虚警概率 雷达 

分 类 号：TN952[电子电信—信号与信息处理]