期刊文献+

一种新的基于删除平均和单元平均的恒虚警率检测器 被引量:5

A New CFAR Detector Based on Censored Mean and Cell Average
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摘要 基于删除平均(CM)和单元平均(CA)提出了一种新型的恒虚警率检测器(CMCAM-CFAR),它采用CM和CA产生局部估计,再对二者平均实现对杂波功率估计。在SwerlingⅡ型目标假设和均匀背景下,推导出了它的检测概率(Pd)、虚警概率(Pfa)和平均判决阈值(ADT)的解析表达式,并与有序统计(OS)恒虚警率(CFAR)检测器进行了比较。分析结果表明在均匀背景和多目标环境下CMCAM-CFAR检测器的性能均优于OS-CFAR检测器的性能。 A new CFAR detector(CMCAM) based on censored mean(CM) and cell average(CA) is proposed in this paper. Ln this detector the mean value of the local estimations of CM and CA is taken as the noise power estimationUnder Swerling Ⅱand homogeneous background assumption,the analytic expressions of Pd,Pfa and ADT are derived for the detectorThe results show that the performance of CMCAM-CFAR detector is better than that of OS-CFAR detector in homogeneous background and multi-target situation
出处 《空军工程大学学报(自然科学版)》 CSCD 2003年第1期26-29,共4页 Journal of Air Force Engineering University(Natural Science Edition)
关键词 恒虚警率检测器 删除平均 单元平均 检测性能 检测概率 雷达自动检测 censored mean cell average CFAR detection performance
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参考文献2

  • 1何友 关键.雷达自动检测与恒虚警处理[M].北京:清华大学出版社,1998..
  • 2唐京海,王晟达,陈国华.一种混合型CFAR处理方法[J].空军工程大学学报(自然科学版),2001,2(1):62-65. 被引量:2

二级参考文献4

  • 1[2]Finn H M,Johson R S. Adaptive Detection Mode with Threshold Control as a Function of Spatially Sampled Clutter-lev-el Estimates[J]. RCA Review,1968,29(3) :414 - 464.
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  • 4[5]Uner M K,Varshney P K. Distributed CFAR Detection in Homogeneons and Homogeneous and Nonhomogeneous Back-grounds[J]. IEEE Trans on AES, 1996,32(1) :84 - 96.

共引文献10

同被引文献25

  • 1何友,关键.一种基于排序和平均的新恒虚警检测器[J].现代雷达,1995,17(4):32-36. 被引量:12
  • 2孟祥伟,何友.一种新的基于有序统计和剔除平均的恒虚警检测器[J].现代雷达,1996,18(1):96-104. 被引量:3
  • 3何友 关键.雷达自动检测与恒虚警处理[M].北京:清华大学出版社,1998..
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  • 9HE You, MENG Xiangwei. Performance of A New Greatest of Selection CFAR Detector Based on Order Statistics and Censored Mean[ C ]//The Third International Conference on Signal Processing. Beijing: [ s. n ], 1996:565 -567.
  • 10Richard J T,Dillard G M.Adaptive Detection Algorithm for Multiple Target Situation[J].IEEE Trans on AES,1977,13(4):338-343.

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