Title | Spatio-temporal joint oversampling-downsampling technique for ultra-high resolution fiber optic distributed acoustic sensing |
Author | |
Corresponding Author | Sun, Qizhen |
Publication Years | 2022-08-01
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DOI | |
Source Title | |
ISSN | 1094-4087
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Volume | 30Issue:16 |
Abstract | In order to suppress the noise of the coherent fiber distributed acoustic sensing (DAS) system, the spatio-temporal joint oversampling-downsampling technique is proposed. The spatial oversampling is used for artificially dense sampling, whose spacing is far less than the target spatial resolution. Then the spatial downsampling performed by the average of multiple differential sub-vectors is utilized to reduce the influence of noise vectors, which could completely eliminate the interfere fading without increasing any system complexity and introducing any crosstalk. Meanwhile, the temporal oversampling-downsampling is analyzed from the perspective of theory and simulation, demonstrating that the noise floor will decrease with the increase of downsampling coefficient. The temporal oversampling is carried out to expand the noise distribution bandwidth and ensure the correct quantization of the noise frequency. Then the temporal downsampling of differential phase reconstruction is utilized to recover the target bandwidth and reduce the out-of-band noise. The experimental results prove that the noise floor is inversely correlated with the spatiotemporal downsampling factors. The strain resolution of the DAS system with the proposed scheme can reach 2.58p epsilon/root Hz@ 100Hz-500Hz and 9.47p epsilon/root Hz@ 10Hz under the condition of DC-500Hz target bandwidth, as well as the probability of the large-noise sensing channels is greatly reduced from 44.32% to 0%. Moreover, the demodulated SNR of dynamic signal is improved by 20.8dB compared with the traditional method. Without any crosstalk, the noise floor is optimized 8dB lower than the averaging technique. Based on the proposed method, the high-performance DAS system has significant competitiveness in the applications with the demand of high-precision and high-sensitivity, such as passive-source seismic imaging and VSP exploration. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement |
URL | [Source Record] |
Indexed By | |
Language | English
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SUSTech Authorship | Non-SUSTech
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Funding Project | National Natural Science Foundation of China["61775072","61922033"]
; National Key Research and Development Program of China[2018YFB2100902]
; Fundamental Research Funds for the Central Universities[HUST:2021JYCXJJ036]
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WOS Research Area | Optics
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WOS Subject | Optics
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WOS Accession No | WOS:000836698500111
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Publisher | |
ESI Research Field | PHYSICS
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Data Source | Web of Science
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Citation statistics |
Cited Times [WOS]:0
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Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/382310 |
Department | Department of Electrical and Electronic Engineering |
Affiliation | 1.Huazhong Univ Sci & Technol, Sch Opt & Elect Informat, Wuhan Natl Lab Optoelect, Natl Engn Lab Next Generat Internet Access Syst, Wuhan 430074, Peoples R China 2.HUST Wuxi Res Inst, Wuxi 214174, Jiangsu, Peoples R China 3.Southern Univ Sci & Technol, Dept Elect & Elect Engn, Shenzhen 518055, Peoples R China 4.Huazhong Univ Sci & Technol, PGMF, Wuhan 430074, Peoples R China 5.Huazhong Univ Sci & Technol, Sch Phys, Wuhan 430074, Peoples R China |
Recommended Citation GB/T 7714 |
Li, Hao,Fan, Cunzheng,Shi, Zhengxuan,et al. Spatio-temporal joint oversampling-downsampling technique for ultra-high resolution fiber optic distributed acoustic sensing[J]. OPTICS EXPRESS,2022,30(16).
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APA |
Li, Hao.,Fan, Cunzheng.,Shi, Zhengxuan.,Yan, Baoqiang.,Chen, Junfeng.,...&Sun, Qizhen.(2022).Spatio-temporal joint oversampling-downsampling technique for ultra-high resolution fiber optic distributed acoustic sensing.OPTICS EXPRESS,30(16).
|
MLA |
Li, Hao,et al."Spatio-temporal joint oversampling-downsampling technique for ultra-high resolution fiber optic distributed acoustic sensing".OPTICS EXPRESS 30.16(2022).
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