Beyond a 10<sup>7</sup> range-resolution<sup>−1</sup> product in an OFDR based on a periodic phase noise estimation method
Chen Zou, Cuofu Lin, Tieliang Mou, Zhangjun Yu, Yunlong Zhu, Yao Zhu, Fanyang Dang, Yonggui Yuan, Jun Yang, Yuncai Wang, Yuwen Qin
Abstract
We present and demonstrate a method based on a periodic phase noise estimation in an optical frequency domain reflectometry (OFDR) capable of a beyond 10 7 range-resolution −1 product (RRP) for the first time, which corresponds to 2.5 × improvement compared with the state-of-the-art. The moving average filter is employed to suppress the amplification of noise in the derivation process. Further, with the help of a third-order Taylor expansion, this method provides a highly precise estimation of periodic phase noise, which is the main factor impacting the performance of OFDR systems with medium-to-long measurement range combined with a submillimeter spatial resolution. A spatial resolution within 535 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi>μ</mml:mi> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mtext>m</mml:mtext> </mml:mrow> </mml:mrow> </mml:math> over the measurement range of 8 km is obtained. The proposed method offers a promising technique for fiber network monitoring and sensing applications.