期刊文献+

基于局部检测统计量的分布式CFAR检测理论研究 被引量:1

Distributed CFAR Detector Based on Local Test Statistics
下载PDF
导出
摘要 本文系统研究了融合中心接收局部检测统计量的分布式CFAR检测技术。在假设局部检测器背景杂波功率水平相同以及不同传感器测试单元之间服从独立同分布的前提下,首先推导了局部采用单元平均(CA)检测器时融合中心的检测概率与虚警概率的解析表达式,在此基础上利用Laplace变换的频域微分性质,将其推广到局部采用其它检测器,获得了普适性的融合方法,可适用于局部采用任意数量、形式的均值(ML)类和有序统计量(OS)类CFAR检测器时的情形,避免了传统的融合中心采用MOS类方法时所需要的局部信杂比相同的假设,实验结果表明了算法的有效性。 This paper studies the design of distributed constant false alarm rate (CFAR) detection systems where the fusing cen- ter receives all of the local test statistics. On the assumption that the clutter power level of the background in each local detector is iden- tical and the returns of the test ceils of different sensors are all independent and identically distributed, we first work out the closed-form expressions of the probabilities of detection (PD) and probabilities of false alarm (PFA) for the fusing center when the local processors use cell average (CA) detectors. By using the differential characteristics of frequency-domain in Laplace transform the universal fusing method is extended to other local CFAR detectors such as maximum likely (ML) and ordered statistic (OS) detectors of any amount or form. This method successfully avoids the assumption of equivalent signal-to-clutter ratio (SCR) in local detectors for traditional fusing center which uses MOS method. The experimental resuhs indicate the validity of the new algorithm proposed in the paper.
作者 魏玺章 黎湘
出处 《信号处理》 CSCD 北大核心 2010年第8期1121-1125,共5页 Journal of Signal Processing
基金 国家杰出青年科学基金(60025102)资助课题
关键词 分布式检测 CFAR 统计量 Distributed Detection CFAR statistic
  • 相关文献

参考文献10

  • 1M. Magarini, A. Spalvieri. Optimization of distributed detection systems under the minimum average misclassification risk criterion. IEEE Trans on IT, vol 46, 2000,1649- 1653.
  • 2廖东平,魏玺章,黎湘,庄钊文.相关条件下基于N-P准则的分布式检测理论研究[J].信号处理,2006,22(4):511-514. 被引量:1
  • 3Ermis, E.B. , Saligrama, V. Distributed Detection in Sensor Networks With Limited Range Muhimodal Sensors. IEEE Transactions on SP, vol58, 2010,843-858.
  • 4Jian Guan, Ying-Ning Peng, You He, Xiang-Wei Meng. Three types of distributed CFAR detection based on local test statistic. IEEE Transactions on AES, Vol 38,2002, 278 -288.
  • 5H. Amirmehrabi, R. Viswanathan. A new distributed constant false alarm rate detector. IEEE Trans on AES, vol. 33, 1997, 85-97.
  • 6C. H. Gowda, R. Viswanathan, Performance of distributed CFAR test under various clutter amplitudes, IEEE Trans on AES, vol. 35, 1999, 1410-1419.
  • 7A. Mathur, P. K. Willett. Local SNR considerations in decentralized CFAR detection. IEEE Trans on AES, vol. 34, 1998,13-22.
  • 8Guan Jian, He You, Peng Ying-Ning, Distributed CFAR detector based on local test statistic, Signal Processing, vol. 80,2000,373-379.
  • 9A. Mathur, P. K. Willett, Local SNR considerations in decentralized CFAR detection, IEEE Tran,~ on AES, 1998, 34 : 13-22.
  • 10沈永欢,梁在中,许履瑚等.实用数学手册,科学出版社,1999.

二级参考文献6

  • 1Z. Chair, P. K. Varsheney, Optimum Data Fusion in Multiple Sensor Detection Systems, IEEE Transactions on Aerospace and Electronic Systems, 1986,22 (1):98 -101.
  • 2S. C. A. Thomopoulos, R. Viswanathan, D. K. Bougoulias,Optimal Decision Fusion in Multiple Sensor Systems, IEEE Transactions on Aerospace and Electronic Systems, 1987,23(5) :644 -653.
  • 3G. S. Lauer, N. R. Sandell, Jr. , Distributed Detection with Waveform Observations: Correlated Observation Processes,Proceedings of ACC, 1982:812 - 819.
  • 4V. Aalo, R. Viswanathan, On Distributed Detection with Correlated Senser: Two Examples, IEEE Transactions on Aerospace and Electronic Systems, 1989,25 ( 3 ) : 414 -421.
  • 5E. Drakopoulos, C. C. Lee, Optimum Multisensor Fusion of Correlated Local Decisions, IEEE Transactions on Aerospace and Electronic Systems, 1991,27 (4) :593 - 605.
  • 6N. S. V. Rao, Distributed Decision Fusion Using Empirical Estimation,IEEE Transactions on Aerospace and Electronic Systems, 1997,33 (4) : 1106 - 1114.

同被引文献9

  • 1Clark J M C, Kountouriotis P A, Vinter R B. A Methodology for Incorporating the Doppler Blind Zone in Target Tracking Algorithms [J ].The 13th International Conference on Infor- mation Fusion Proceedings.2010( 8 ) : 1481-1488.
  • 2Thomopoulos S, Viswanathan R, Bougoulias D.Optimal Dis- tributed Decision Fusion [J].IEEE Trans, on Aero, and Elec, 1989,25(6):761-765.
  • 3Ansari N, Chen J. G,Zhang Y Z, Adaptive Decision Fusion for Unequiprobable Sources [J]. IEE Proceedings of Radar sonar and Navigation. 1997,144( 3 ):105-111.
  • 4Yan Q,Blum R S.Distributed Signal Detection under the Neyman-Pearson Criterion [J].IEEE Transactions on Infor- mation Theory, 2001,47 (4) : 1368-1377.
  • 5Kelly E J. An Adaptive Detection Algorithm [J].IEEE Trans. 1986,22( 1 ) : 115-127.
  • 6李涛,冯大政,夏宇垠.基于EM算法和信息论准则的分布式目标检测算法[J].电子与信息学报,2010,32(4):908-912. 被引量:3
  • 7战立晓,汤子跃,朱振波,付莹.空地双基地雷达杂波建模与特性分析[J].数据采集与处理,2010,25(6):777-782. 被引量:6
  • 8蒋铁珍.分布式检测多目标融合算法研究[J].中国电子科学研究院学报,2010,5(6):594-598. 被引量:5
  • 9董鹏曙,张朝伟,金加根,谢幼才.分布式网络雷达检测融合处理算法[J].雷达科学与技术,2011,9(4):347-350. 被引量:7

引证文献1

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部