Enhancement of signal-to-noise ratio in Brillouin optical time domain analyzers by dual-probe detection

Iribas, Haritz (Institute of Smart Cities, Universidad Publica de Navarra, Iruñea, Spain) ; Loayssa, Alayn (Institute of Smart Cities, Universidad Publica de Navarra, Iruñea, Spain) ; Sauser, Florian (School of Engineering – HE-Arc Ingénierie, HES-SO // University of Applied Sciences Western Switzerland) ; Llera, Miguel (School of Engineering – HE-Arc Ingénierie, HES-SO // University of Applied Sciences Western Switzerland) ; Le Floch, Sébastien (School of Engineering – HE-Arc Ingénierie, HES-SO // University of Applied Sciences Western Switzerland)

We demonstrate a simple technique to enhance the signal-to-noise ratio (SNR) in Brillouin optical time-domain analysis sensors by the addition of gain and loss processes. The technique is based on the shift of the pump pulse optical frequency in a double-sideband probe system, so that the gain and loss processes take place at different frequencies. In this manner, the loss and the gain do not cancel each other out, and it makes possible to take advantage of both informations at the same time, obtaining an improvement of 3 dB on the SNR. Furthermore, the technique does not need an optical filtering, so that larger improvement on SNR and a simplification of the setup are obtained. The method is experimentally demonstrated in a 101 km fiber spool, obtaining a measurement uncertainty of 2.6 MHz (2σ) at the worst-contrast position for 2 m spatial resolution. This leads, to the best of our knowledge, to the highest figure-of-merit in a BOTDA without using coding or raman amplification.


Type de conférence:
full paper
Faculté:
Ingénierie et Architecture
Ecole:
HE-Arc Ingénierie
Institut:
Aucun institut
Classification:
Ingénierie
Adresse bibliogr.:
Jeju, Korea, Republic of, 24-28 April 2018
Date:
2017-04
Jeju, Korea, Republic of
24-28 April 2018
Veröffentlicht in:
Proceedings of the 25th International Conference on Optical Fiber Sensors, 24-28 April 2017, Jeju, Korea, Republic of
DOI:
ISSN:
0277786X
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 Datensatz erzeugt am 2019-03-26, letzte Änderung am 2019-04-23


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