Sub-spatial resolution position estimation for optical fibre sensing applications

Beitrag bei einer Tagung

Details zur Publikation

Autorinnen und Autoren: Zibar D, Werzinger S, Schmauß B
Jahr der Veröffentlichung: 2017
Tagungsband: IEEE Sensors Conference
Sprache: Englisch


Methods from machine learning community are employed for estimating the
position of fibre Bragg gratings in an array. Using the conventional
methods for position estimation, based on inverse discrete Fourier
transform (IDFT), it is required that two-point spatial resolution is
less than gratings' spacing. However, we show that by employing
statistical inference methods in combination with adaptive gradient
algorithm, it is still possible to estimate the grating positions even
though this requirement is violated. No prior knowledge of the
reflection coefficients is needed as the joint estimation of reflection
coefficients and the positions is performed. From the practical point of
view, we can demonstrate the reduction of the interrogator's bandwidth
by factor of 2. The technique is demonstrated for incoherent optical
frequency domain reflectometry (IOFDR). However, the approach is
applicable to any other OFDR technique where bandwidth-resolution
limitations of IDFT apply.

FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Schmauß, Bernhard Prof. Dr.-Ing.
Professur für Hochfrequenztechnik mit dem Schwerpunkt Optische Hochfrequenztechnik und Photonik
Werzinger, Stefan
Lehrstuhl für Hochfrequenztechnik
Zibar, Darko
Erlangen Graduate School in Advanced Optical Technologies


Zibar, D., Werzinger, S., & Schmauß, B. (2017). Sub-spatial resolution position estimation for optical fibre sensing applications. In IEEE Sensors Conference. Glasgow, GB.

Zibar, Darko, Stefan Werzinger, and Bernhard Schmauß. "Sub-spatial resolution position estimation for optical fibre sensing applications." Proceedings of the IEEE Sensors Conference, Glasgow, GB 2017.


Zuletzt aktualisiert 2018-22-10 um 01:40