基于样本相关的SMN-MUSIC算法的谐波恢复方法  

Sample correlation-based SMN-MUSIC method for harmonic restoration

作　　者：石屹然[1] 曲思凝 齐金伟 赵洋[1] SHI Yi-ran;QU Si-ning;QI Jin-wei;ZHAO Yang(College of Communication Engineering,Jilin University,Changchun 130022,China)

机构地区：[1]吉林大学通信工程学院,长春130022

出　　处：《吉林大学学报（工学版）》2022年第5期1153-1160,共8页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金重大项目(51835006)。

摘　　要：和高斯混合噪声背景下的谐波信号频率估计精度问题一直都是信号处理领域的研究热点和难点,但现有的互相关算子和分数低阶统计量类算子均存在噪声抑制能力差、计算度复杂以及估计精度不高的问题。针对上述问题,本文提出了基于样本相关的SMN-MUSIC算法。首先,利用样本相关算法,实现对α和高斯混合噪声的抑制;然后,对噪声子空间进行最小范数矢量计算,根据其与谐波信号频率的正交特性,提出SMN-MUSIC算法,实现了高效的谐波参数估计;最后,对基于样本相关的SMN-MUSIC算法的无偏一致估计性进行理论推导证明。本文算法降低了噪声奇异矢量误差敏感,减少了谱峰搜索计算量,计算机仿真结果证明了该算法的有效性。The accuracy of harmonic signal frequency estimation in hybrid noise has always been a research hotspot and difficulty in the field of signal processing.However,the existing cross-correlation operators and fractional low-order statistics operators have poor noise suppression capabilities,complexity calculation and low estimation accuracy.A sample correlation function’s SMN-MUSIC method was proposed regarding the issues above.Firstly,sample correlation algorithm is used to achieve the suppression of hybrid noise.Secondly,the minimum norm vector calculation of the noise subspace is carried out.According to the orthogonal characteristic with harmonic signal frequency,the SMN-MUSIC algorithm is proposed to achieve efficient harmonic parameter estimation.Finally,the characteristic of unbiased consistent estimator has been proved based on sample correlation function’s SMN-MUSIC method.The algorithm reduces the sensitivity of noise singular vector errors and the amount of spectral peak search calculations.The simulation proves the effectiveness of the algorithm.

关 键 词：谐波恢复 α噪声 样本相关函数 无偏一致估计 

分 类 号：TN911.7[电子电信—通信与信息系统]