Author(s): Ma, LL (Ma, Lilong); Xu, TW (Xu, Tuanwei); Cao, K (Cao, Kai); Jiang, YH (Jiang, Yinghao); Deng, DM (Deng, Dimin); Li, F (Li, Fang)

Source: SENSORS Volume: 22 Issue: 4 Article Number: 1670 DOI: 10.3390/s22041670 Published: FEB 2022

Abstract: The key point on analyzing the data stream measured by fiber optic distributed acoustic sensing (DAS) is signal activity detection separating measured signals from environmental noise. The inability to calculate the threshold for signal activity detection accurately and efficiently without affecting the measured signals is a bottleneck problem for current methods. In this article, a novel signal activity detection method with the adaptive-calculated threshold is proposed to solve the problem. With the analysis of the time-varying random noise's statistical commonality and the short-term energy (STE) of real-time data stream, the top range of the total STE distribution of the noise is found accurately for real-time data stream's ascending STE, thus the adaptive dividing level of signals and noise is obtained as the threshold. Experiments are implemented with simulated database and urban field database with complex noise. The average detection accuracies of the two databases are 97.34% and 90.94% only consuming 0.0057 s for a data stream of 10 s, which demonstrates the proposed method is accurate and high efficiency for signal activity detection.

Accession Number: WOS:000771612300001

PubMed ID: 35214572

eISSN: 1424-8220

Full Text: https://www.mdpi.com/1424-8220/22/4/1670