分布式声传感:如何充分利用瑞利背散射能量?

A. Eyal, H. Gabai, I. Shpatz
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引用次数: 3

摘要

相干衰落噪声(又称散斑噪声)影响分布式声传感系统的信噪比和灵敏度,使其成为位置和时间的随机过程。与散斑噪声一样,DAS信噪比的统计分布特别宽,其标准差(STD)大致等于其均值(σSNR/ < SNR > 0.89)。SNR的交易分辨率可能会提高平均SNR,但不一定会缩小其分布。本文介绍了一种既能提高信噪比(通过牺牲分辨率)又能缩小分布的新方法。该方法是在获取传感光纤高分辨率复杂后向散射曲线的基础上,利用其计算保留相位变化信息的光纤复杂功率曲线,并对功率曲线进行滤波。通过计算机仿真验证了该方法的有效性,结果表明该方法的分布可缩小到σSNR/ < SNR > < 0.2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed acoustic sensing: How to make the best out of the Rayleigh-backscattered energy?
Coherent fading noise (also known as speckle noise) affects the SNR and sensitivity of Distributed Acoustic Sensing (DAS) systems and makes them random processes of position and time. As in speckle noise, the statistical distribution of DAS SNR is particularly wide and its standard deviation (STD) roughly equals its mean (σSNR/〈SNR〉 œ 0.89). Trading resolution for SNR may improve the mean SNR but not necessarily narrow its distribution. Here a new approach to achieve both SNR improvement (by sacrificing resolution) and narrowing of the distribution is introduced. The method is based on acquiring high resolution complex backscatter profiles of the sensing fiber, using them to compute complex power profiles of the fiber which retain phase variation information and filtering of the power profiles. The approach is tested via a computer simulation and demonstrates distribution narrowing up to σSNR/〈SNR〉 < 0.2.
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