Evidence map›Paper›PMID 41682520›Full record

ArticleSensors (Basel, Switzerland)2026

High-Resolution OFDR with All Grating Fiber Combining Phase Demodulation and Cross-Correlation Methods.

Yanlin Liu, Yang Luo, Xiangpeng Xiao, Zhijun Yan, Yu Qin, Yichun Shen, Feng Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yanlin LiuKey Laboratory of Intelligent Optical Sensing and Manipulation (MoE), Nanjing University, Nanjing 210023, China.
Yang LuoKey Laboratory of Intelligent Optical Sensing and Manipulation (MoE), Nanjing University, Nanjing 210023, China.
Xiangpeng XiaoSchool of Optical and Electronic Information, Huazhong University of Science Technology, Wuhan 430074, China.
Zhijun YanSchool of Optical and Electronic Information, Huazhong University of Science Technology, Wuhan 430074, China.
Yu QinAdvanced Fiber Devices and Systems Group, Key Laboratory of Micro and Nano Photonic Structures (MoE), College of Future Information Technology, Fudan University, Shanghai 200433, China.
Yichun ShenAdvanced Fiber Devices and Systems Group, Key Laboratory of Micro and Nano Photonic Structures (MoE), College of Future Information Technology, Fudan University, Shanghai 200433, China.
Feng WangKey Laboratory of Intelligent Optical Sensing and Manipulation (MoE), Nanjing University, Nanjing 210023, China.

Funding

Frontier Technologies R&D Program of Jiangsu BF2024036Frontier Technologies Research Program of Suzhou SYG202303Key R&D Program of Jiangsu BE2023083
6 · The paper itself

Abstract

Spatial resolution is a critical parameter for optical frequency domain reflectometry (OFDR). Phase-sensitive OFDR (Φ-OFDR) measures strain by detecting phase variations between adjacent sampling points, having the potential to achieve the theoretical limitation of spatial resolution. However, the results of Φ-OFDR suffer from large fluctuations due to multiple types of noise, including coherent fading and system noise. This work presents an OFDR-based strain sensing method that combines phase demodulation with cross-correlation analysis to achieve high spatial resolution. In the phase demodulation, the frequency-shift averaging (FSAV) and rotating vector summation (RVS) algorithms are first employed to suppress coherent fading noise and achieve accurate strain localization. Then the cross-correlation approach with an adaptive window is proposed. Guided by the accurate strain boundary obtained from phase demodulation, the length and position of the cross-correlation window are automatically adjusted to fit for continuous and uniform strain regions. As a result, an accurate and complete strain distribution along the entire fiber is finally obtained. The experimental results show that, within a strain range of 100-700 με, the method achieves a spatial resolution of 0.27 mm for the strain boundary, with a root-mean-square error approaching 0.94%. The processing time reaches approximately 0.035 s, with a demodulation length of 1.6 m. The proposed approach offers precise spatial localization of the strain boundary and stable strain measurement, demonstrating its potential for high-resolution OFDR-based sensing applications.

Indexed as

cross-correlationOFDRphase demodulationstrain sensing

Identifiers

PMID41682520
PMCPMC12899954

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.