Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/95334
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Photonics Research Centre | en_US |
| dc.contributor | Department of Electrical Engineering | en_US |
| dc.creator | Adeel, M | en_US |
| dc.creator | Tejedor, J | en_US |
| dc.creator | Macias-Guarasa, J | en_US |
| dc.creator | Lu, C | en_US |
| dc.date.accessioned | 2022-09-19T01:59:45Z | - |
| dc.date.available | 2022-09-19T01:59:45Z | - |
| dc.identifier.issn | 1041-1135 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/95334 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
| dc.rights | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
| dc.rights | The following publication M. Adeel, J. Tejedor, J. Macias-Guarasa and C. Lu, "Improved Perturbation Detection in Direct Detected φ-OTDR Systems using Matched Filtering," in IEEE Photonics Technology Letters, vol. 31, no. 21, pp. 1689-1692, 1 Nov.1, 2019 is available at https://doi.org/10.1109/LPT.2019.2940297. | en_US |
| dc.subject | Distributed acoustic sensing | en_US |
| dc.subject | Perturbation detection | en_US |
| dc.subject | Phase-OTDR | en_US |
| dc.title | Improved perturbation detection in direct detected φ-OTDR systems using matched filtering | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 1689 | en_US |
| dc.identifier.epage | 1692 | en_US |
| dc.identifier.volume | 31 | en_US |
| dc.identifier.issue | 21 | en_US |
| dc.identifier.doi | 10.1109/LPT.2019.2940297 | en_US |
| dcterms.abstract | Nuisance Alarm Rate (NAR) is critical in φ-OTDR perturbation detection systems. We present in this letter a novel matched filtering-based feature extractor which aims to noise reduction so that the detection system gets improved performance. This feature extractor requires a small number of data vectors to be acquired which is combined with a random forest-based machine learning strategy to significantly reduce the NAR. In addition, since the number of data vectors is small, this system can also be useful for time-sensitive detection applications. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | IEEE photonics technology letters, 1 Nov. 2019, v. 31, no. 21, 8830461, p. 1689-1692 | en_US |
| dcterms.isPartOf | IEEE photonics technology letters | en_US |
| dcterms.issued | 2019-11-01 | - |
| dc.identifier.scopus | 2-s2.0-85077686620 | - |
| dc.identifier.eissn | 1941-0174 | en_US |
| dc.identifier.artn | 8830461 | en_US |
| dc.description.validate | 202209 bcvc | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | RGC-B2-0359 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Improved_Perturbation_Detection.pdf | Pre-Published version | 1.26 MB | Adobe PDF | View/Open |
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