电能质量信号压缩采样匹配跟踪算法研究Research on CoSaSAMP Algorithm for Power Quality Signal
刘传洋,孙佐,刘景景,方曙东,李春国,宋康
摘要(Abstract)：
电能质量信号具有实时随机性,针对匹配跟踪算法在稀疏度未知的情况下难以精确重构电能质量信号的缺陷问题,提出了稀疏度自适应的压缩采样匹配追踪算法。引入稀疏度估计方法提前对信号的初始稀疏度进行迭代估计,利用递归思想通过残差变化动态调整稀疏度逼近信号的真实稀疏度,通过最小二乘法重构出电能质量信号最优估值。实验结果表明,在测量矩阵为二元块对角矩阵的基础上,所提出的算法与压缩采样匹配跟踪算法与自适应匹配追踪算法相比,信噪比提高了10～20 dB,具有抗干扰能力强、重构精度高的优点。
关键词(KeyWords)： 电能质量;压缩采样;自适应;递归;稀疏度
基金项目(Foundation): 国家自然科学基金资助项目(NSFC61671144);; 山东省自然科学基金资助项目(ZR2017BF028);; 安徽省优秀拔尖人才基金资助项目(GXYQ2019109、GXGNFX2019056);; 池州学院研究基金资助项目(2018XJPKC12、2017XWTXM07)
作者(Author): 刘传洋,孙佐,刘景景,方曙东,李春国,宋康
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