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基于局部观测信噪比的新分布式CFAR检测 被引量:4

New distributed CFAR detection scheme based on SNR of local observations
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摘要 为了提高基于二元局部判决的分布式CFAR检测的性能,提出一类新的基于局部观测信噪比的分布式CFAR检测方案(称为R类方案)。其特点是以CFAR算法做局部处理以形成局部观测的信噪比估值,然后将其传送给数据融合中心。相对于S+OS,R类方案不仅使局部处理器和数据融合中心间的通信量减少了一半,而且对局部观测的要求也比S+OS宽松。在三种典型背景环境中和两个局部处理器的条件下,分析了其中一种方案:OS-R-CA,推导出了它的检测和虚警性能的闭形解,并将其与COS,S+OS等分布式CFAR检测进行了性能比较。结果表明,OS-R-CA的检测性能和虚警控制能力保持在了与S+OS接近的水平。 A new type of distributed constant false alarm rate (CFAR) scheme based on the ratio of signal to noise (SNR) of local observations (referred as R type scheme) is presented, to improve the performance of distributed CFAR detection based on binary local decision. Its characteristics are that CFAR algorithms are used in local processor to form the estimation of SNR of local observations, and then the estimation is transmitted to the data fusion center (DFC). Compared with the S+OS, the R type scheme not only saves a half of the amount of data transmitted between local processor (LP) and DFC, but also overcomes the drawback of S+OS, which is not suitable to the practical use. In three classical backgrounds, it analyses one of them, OS R CA for two sensor network, and derives the closed form solutions of detection and false alarm performance, and compares its performance with the COS and S+OS distributed CFAR detections. Result shows that the detection and false alarm performance of OS R CA remains at the level similar to that of S+OS.
出处 《清华大学学报(自然科学版)》 EI CAS CSCD 北大核心 1999年第1期51-54,共4页 Journal of Tsinghua University(Science and Technology)
基金 国防科研基金
关键词 分布式检测 杂波边缘 信号检测 CFAR检测 信噪比 distributed detection homogeneous background multiple targets clutter edge 
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参考文献3

  • 1Meng Xiangwei,IEEE Proc 1998 Int Sympo Radar,1998年 被引量:1
  • 2He You,IEEE Int Conf SMC,1996年 被引量:1
  • 3Longo M,IEEE Trans Aerosp Electron Syst,1996年,32卷,4期,1257页 被引量:1

同被引文献23

  • 1许江湖,张明敏,胡金华.混响背景下基于自动删除算法的恒虚警检测器[J].电子与信息学报,2007,29(3):639-642. 被引量:2
  • 2郭启俊,刘劲,刘宏伟.基于时频融合的分布式目标的恒虚警率检测[J].雷达科学与技术,2007,5(1):65-68. 被引量:4
  • 3Anna L Dzvonokovskaya, Hermann Rohling. Ship Detection with Adaptive Power Regression Thresholding for HF Radar. Hamburg University of Technology, Germany, 2007. 被引量:1
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