Evidence map›Paper›PMID 41398165›Full record

ArticleNature communications2025

70 km long-range Raman distributed optical fibre sensing through enhanced anti-distortion coding and waveform reconstruction.

Fan Zhang, Jian Li, Lulei Li, Kangyi Cao, Mingjiang Zhang

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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

5 authors.

Fan ZhangCollege of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan, China.ORCID http://orcid.org/0009-0003-4874-5706
Jian LiCollege of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan, China. lijian02@tyut.edu.cn.ORCID http://orcid.org/0009-0004-4126-187X
Lulei LiCollege of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan, China.ORCID http://orcid.org/0009-0002-8298-9432
Kangyi CaoCollege of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan, China.ORCID http://orcid.org/0009-0008-4591-2050
Mingjiang ZhangCollege of Physics and Optoelectronics, Taiyuan University of Technology, Taiyuan, China. zhangmingjiang@tyut.edu.cn.ORCID http://orcid.org/0000-0002-8097-8169

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62475183,62205234,U23A20375
6 · The paper itself

Abstract

The practical implementation of Raman distributed optical fibre sensing has been fundamentally constrained by the inherent low signal-to-noise ratio (SNR), particularly for sensing distance exceeding 30 km. We propose a paradigm that combines enhanced anti-distortion coding processing, advanced Raman scattering waveform reconstruction preprocessing, and Haar wavelet denoising to transcend this physical limitation. The proposed pre-processing framework simultaneously optimises complementary sequences correlation, effectively mitigates disturbances of transient effects and improves sensing performance. The experimental demonstration achieves performance metrics: 70.0 km sensing distance with 1.58 m spatial resolution, while maintaining 0.91 °C measurement accuracy and 5.39 °C temperature resolution. The tripartite synergistic mechanism, consisting of the waveform reconstruction pre-processing framework compensating for and suppressing transient effects, coding gain improving the baseline SNR, and the Haar wavelet transform removing residual noise, breaks through the theoretical trade-off constraint between SNR and sensing distance in traditional schemes. The proposed approach demonstrates a potential for application in the fields of long-range infrastructure monitoring and environmental sensing.

Identifiers

PMID41398165
PMCPMC12820281

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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.