Proposal of correlation-dip-based optical correlation-domain reflectometry

Conventional distributed measurement methods that employ correlation-domain techniques typically use a “correlation peak” as the measurement point. In this work, we propose and experimentally demonstrate a novel form of optical correlation-domain reflectometry that targets the “correlation dip,” located between two correlation peaks. As the reflected spectrum observed at the correlation dip exhibits its maximum bandwidth, we can selectively detect the reflection from the fiber under test by measuring the power in that broad frequency band. We verify the basic operation of this technique experimentally.

Authors

Institutions

Publication Details

Published
2025-05-22
DOI
https://doi.org/10.1117/12.3062560
Primary Topic
Advanced Fiber Optic Sensors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Proposal of correlation-dip-based optical correlation-domain reflectometry

Yosuke Mizuno, Haruyuki Kubota
Advanced Fiber Optic Sensors
article

Proposal of correlation-dip-based optical correlation-domain reflectometry

Yosuke Mizuno, Haruyuki Kubota
article en

Abstract

Conventional distributed measurement methods that employ correlation-domain techniques typically use a “correlation peak” as the measurement point. In this work, we propose and experimentally demonstrate a novel form of optical correlation-domain reflectometry that targets the “correlation dip,” located between two correlation peaks. As the reflected spectrum observed at the correlation dip exhibits its maximum bandwidth, we can selectively detect the reflection from the fiber under test by measuring the power in that broad frequency band. We verify the basic operation of this technique experimentally.

Yokohama National University (JP)
Openalex Percentile: Top 91%
Advanced Fiber Optic Sensors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.