自适应奇异值分解瞬变信号检测研究

Detection of Transient Signal Based on Adaptive Singular Value Decomposition

该文介绍了奇异值分解检测信号的原理,研究了井下电磁脉冲数据传输中接收到的瞬变信号和噪声的奇异值分布特性,提出了相邻奇异值增量的概念,并根据瞬变信号和噪声相邻奇异值增量的不同,区分信号与噪声。在此基础上,提出了自适应选择主奇异值个数的奇异值分解检测瞬变信号的方法,并给出该方法检测瞬变信号的具体流程。仿真结果表明,与传统奇异值分解相比,该方法检测微弱瞬变信号更准确。

This paper introduces the principle of signal detection by Singular Value Decomposition （SVD）, and discusses the singular value’s distribution characteristics of the transient signal and Gauss white noise which received from electromagnetic-pulse along the well bore. Then the definition of singular value increment is given, and the signal is distinguished easily from noise according to those singular value increment’s differences. On this basis, an adaptive singular value decomposition method based on selection of main singular value using singular value increment is proposed for the detection of transient signal, and the detailed flowchart of the method is illustrated. Simulation results demonstrate that, the proposed method has a good effect on distinguishing the transient faint signal from noise and the performance outperforms the typical SVD.