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工程科学与技术:2014,46(6):122-127
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噪声功率不确定模型下基于CFAR准则的能量检测门限优化算法
(1.解放军理工大学通信工程学院;2.解放军信息工程大学信息系统工程学院;3.重庆邮电大学 个人通信研究所)
ACFAR-basedThresholdOptimizationAlgorithmforEnergyDetection UnderNoisePowerUncertainty
(1.Inst.ofCommunicationsEng.,PLAUniv.ofSci. & Technol.;2.Inst.ofInfo.SystemEng.,PLA Info.Eng.Univ.;3.Inst.ofPersonalCommunications,ChongqingUniv.ofPostsandTelecommunications)
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投稿时间:2014-04-09    修订日期:2014-09-12
中文摘要: 针对频谱感知中能量检测器在噪声功率不确定模型下存在门限失配问题,提出一种基于CFAR准则的能量检测门限优化算法(TO-ED),证明存在唯一最优的修正因子可以优化稳健统计方案(RSA)的判决门限;基于RSA的平均虚警概率是关于修正因子的单调函数,利用牛顿二分法实现最优修正因子的快速迭代求解并修正RSA的判决门限。仿真表明:TO-ED算法满足CFAR意义下最优,其理论性能和仿真结果一致;实现鲁棒检测所需信噪比比RSA更低。
Abstract:Threshold mismatch of energy detection (ED) under noise power uncertainty (NPU) model was investigated. A threshold optimization algorithm of ED (TO-ED) was proposed based on constant false alarm ratio (CFAR) criterion. Firstly, for optimizing the threshold of robust statistics approach (RSA) under the condition of CFAR, the unique existence of optimal modified factor was proved. Secondly, since the average false alarm probability of RSA is a monotonic function of modified factor, Newton dichotomy was applied to quick search of this optimal factor. Simulations showed that the performance of TO-ED is consistent with theoretical analysis and its robust detection is realized with a lower signal-to-noise ratio(SNR) comparing with RSA.
文章编号:201400373     中图分类号:    文献标志码:
基金项目:国家自然科学基金资助项目(61172062;60932002);江苏省自然科学基金资助项目(SBK201122196)
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孙有铭,王金龙,张剑,胡小峰,刘洛琨.噪声功率不确定模型下基于CFAR准则的能量检测门限优化算法[J].工程科学与技术,2014,46(6):122-127.
Sun Youming,Wang Jinlong,Zhang Jian,Hu Xiaofeng,Liu Luokun.ACFAR-basedThresholdOptimizationAlgorithmforEnergyDetection UnderNoisePowerUncertainty[J].Advanced Engineering Sciences,2014,46(6):122-127.