基于奇异值分解降噪和幅值加权的互相关时延估计方法  

Correlation Time Delay Estimation Based on Singular Value Decomposition and Amplitude Weighted Cross

作　　者：徐伟龙 梁斌[1] Xu Weilong;Liang Bin(Tianjin Normal University,Tianjin 30080,China)

机构地区：[1]天津师范大学,天津300380

出　　处：《计算机时代》2025年第1期16-19,共4页Computer Era

摘　　要：对于无源时差定位中的互相关算法抗噪声能力弱,准确率低等问题,本文提出了一种先对声源信号进行奇异值分解降噪,再使用幅值加权方法改进的互相关时延算法。先使用奇异值分解降噪提取声源信号的主分量,对信号进行降噪提升信噪比,再用幅值加权扩大互相关功率谱函数频点的幅值,提升时延估计的准确率和可靠性。经仿真实验验证,新算法能准确的计算值时延值,对时延算法的研究有一定的价值。For the problems of poor noise resistance and low accuracy of cross-correlation algorithms in passive time-difference positioning,this paper proposes a method of first performing singular value decomposition denoising on the sound source signal and then using amplitude weighting to improve the cross-correlation delay algorithm.The main component of the sound source signal is first extracted by singular value decomposition noise reduction,the signal noise is reduced to improve the signal-to-noise ratio,and then amplitude weighting is used to expand the amplitude of the frequency point of the inter-correlation power spectral function,which improves the accuracy and reliability of the time-delay estimation.After simulation experiments,the new algorithm can accurately calculate the value of time delay,which is valuable for the research of time delay algorithm.

关 键 词：奇异值分解 信号降噪 幅值加权 互相关算法 时差定位 

分 类 号：TN912.3[电子电信—通信与信息系统]