基于K-S检验的BPSK信号盲处理结果可信性评估

胡国兵, 徐立中, 高燕, 吴珊珊, 居美艳

电子学报 ›› 2014, Vol. 42 ›› Issue (10) : 1882-1886.

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电子学报 ›› 2014, Vol. 42 ›› Issue (10) : 1882-1886. DOI: 10.3969/j.issn.0372-2112.2014.10.002
学术论文

基于K-S检验的BPSK信号盲处理结果可信性评估

  • 胡国兵1,2, 徐立中2, 高燕1, 吴珊珊1, 居美艳2
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Confidence Evaluation for Blind Processing Results of BPSK Signals via Kolmogorov-Smirnov Hypothesis Test

  • HU Guo-bing1,2, XU Li-zhong2, GAO Yan1, WU Shan-shan1, JU Mei-yan2
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文章历史 +

摘要

本文提出了一种基于K-S(Kolmogorov-Smirnov)分布拟合检验的BPSK信号盲处理结果可信性评估算法.首先建立了BPSK信号盲处理结果可信性评估的假设检验模型,而后根据调制识别结果对应的信号模型构造参考信号,提取其与观测信号相关后的相位序列.基于K-S分布拟合检验,比较相位序列概率分布与零假设下特定概率分布是否一致,以判决某次处理结果的可信与否.计算机仿真结果表明,本算法可在较低信噪比条件下,实现对BPSK信号盲处理结果的可信性检验.

Abstract

A confidence test method based on Kolmogorov-Smirnov hypothesis test is proposed to evaluate the blind processing results of BPSK signals.The hypothesis test model is created at first.The reference signals are constructed depending on the certain identified modulation result and the phase series are extracted from the correlation between the reference signals and the observed signals.By computing the empirical cumulative distribution function of the phase series and comparing it with the specific cumulative distribution function of phase series under null hypothesis, the K-S based confidence test is performed.Simulation results show that the proposed method can be used to verify the confidence for blind processing results of BPSK signals at low signal-to-noise ratio.

关键词

盲信号处理 / 可信性评估 / Kolmogorov-Smirnov检验

Key words

blind signal processing / confidence evaluation / Kolmogorov-Smirnov hypothesis test

引用本文

导出引用
胡国兵, 徐立中, 高燕, 吴珊珊, 居美艳. 基于K-S检验的BPSK信号盲处理结果可信性评估[J]. 电子学报, 2014, 42(10): 1882-1886. https://doi.org/10.3969/j.issn.0372-2112.2014.10.002
HU Guo-bing, XU Li-zhong, GAO Yan, WU Shan-shan, JU Mei-yan. Confidence Evaluation for Blind Processing Results of BPSK Signals via Kolmogorov-Smirnov Hypothesis Test[J]. Acta Electronica Sinica, 2014, 42(10): 1882-1886. https://doi.org/10.3969/j.issn.0372-2112.2014.10.002
中图分类号: TN911.6   

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基金

江苏省基础研究计划 (自然科学基金) (No.BK2011837); 江苏省政府留学基金 (No.JS-2007-105); 江苏省"333高层次人才培养工程" (No.BRA2013171)

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