Note: Gaussian mixture model for event recognition in optical time-domain reflectometry based sensing systems

被引：25

作者：

Fedorov, A. K. ^{[1
,2
]}

Anufriev, M. N. ^{[1
,2
]}

Zhirnov, A. A. ^{[1
]}

Stepanov, K. V. ^{[1
]}

Nesterov, E. T. ^{[1
]}

Namiot, D. E. ^{[3
]}

Karasik, V. E. ^{[1
]}

Pnev, A. B. ^{[1
]}

机构：

[1] Bauman Moscow State Tech Univ, 2nd Baumanskaya St 5, Moscow 105005, Russia

[2] DEPHAN, Theoret Dept, Novaya St 100, Moscow 143025, Russia

[3] Moscow MV Lomonosov State Univ, Vorobevy Gory 1, Moscow 119992, Russia

来源：

REVIEW OF SCIENTIFIC INSTRUMENTS | 2016年 / 87卷 / 03期

关键词：

INTRUSION-SENSOR; PHASE-OTDR;

D O I：

10.1063/1.4944417

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

We propose a novel approach to the recognition of particular classes of non-conventional events in signals from phase-sensitive optical time-domain-reflectometry-based sensors. Our algorithmic solution has two main features: filtering aimed at the de-nosing of signals and a Gaussian mixture model to cluster them. We test the proposed algorithm using experimentally measured signals. The results show that two classes of events can be distinguished with the best-case recognition probability close to 0.9 at sufficient numbers of training samples. (C) 2016 AIP Publishing LLC.

引用

页数：3

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