基于haar小波变换的噪声环境下地震检测及到达时间估计

I. Thanasopoulos, J. Avaritsiotis
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引用次数: 4

摘要

本文提出了一种离散小波变换(DWT)方法,用于传感器网络中地震信号的事件检测和到达时间估计。选择Haar小波是因为其计算复杂度低,且在时域具有良好的局域性,这对瞬态信号的分析至关重要。该方法不需要先验地了解信号的频谱特征,因为该算法在获取信号时定义了通过时域特征提取信息的最佳尺度。通过模拟地表地震波传播的计算机程序验证了该算法的性能。仿真结果验证了该方法在源定位应用中的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Seismic detection and time of arrival estimation in noisy environments based on the haar wavelet transform
In this paper we propose a discrete wavelet transform (DWT) method for event detection and estimation of the time of arrival (TOA) of seismic signals in a sensor network. The Haar wavelet is selected for its low computational complexity and its good locality in time domain which is essential for the analysis of transient signals. The proposed method requires no a priori knowledge about the spectral characteristics of the signals, because the algorithm defines the optimum scales for the extraction of information by time-domain features as the signal is acquired. The performance of the algorithm is verified using a computer program that simulates the propagation of surface seismic waves. Simulation results corroborate the suitability of the proposed method for source localization applications.
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