The decrease of overlap between the reference spectrum and measurement spectrum (ReS and MeS) is found to limit the strain measurable range of the optical frequency domain reflectometer (OFDR) and signal-to-noise ratio (SNR) of cross-correlation results. In this Letter, the local similar characteristics of Rayleigh scattering (RS) fingerprint spectrum are discovered and, thus, an improved OFDR based on local similarity of RS spectrum is proposed to ensure the feasibility of the OFDR during measuring a large distribution strain with a high spatial resolution. The normalized length and location of the local spectrum are optimized to obtain a high spectral similarity between the ReS and MeS and achieve a robust suppression on cross-correlation fake peaks and multi-peaks. By this method, four times enhancement of similarity is experimentally achieved, compared to conventional OFDR methods when the measured distribution strain varies from 0 to 3000 μϵ with a 3 mm long fiber gauge. The experimental results verify that it effectively avoids influences of fake peaks and multi-peaks. The advantages of this method are a large strain measurable range, robust performance, a high SNR, and applicability with current OFDR systems.

Multi-core fiber (MCF) has attracted increasing attention for application in distributed fiber sensing owing to its unique properties of independent light transmission in multiple spatial channels. Here, we report a distributed acoustic sensing (DAS) system integrated MCF to suppress coherent fading, which overcomes an inevitable challenge in DAS systems. Because the parallel spatial cores in MCF allow the use of space-division multiplexed (SDM) technology, we propose that fading can be effectively suppressed by merging different signals with the spatial rotated-vector-average (SRVA) method. We theoretically analyze the principle of SRVA in fading suppression, and identify that it can effectively reduce phase noise with preventing phase unwrapping failures. In our experiment, a DAS system with 2.58-km length MCF have been investigated, the fading rate of Rayleigh backscattered signals is effectively reduced by three orders of magnitude and the amplitude fluctuation range is decreased by 21.9 dB. Compared with the conventional spectrum extraction and remix method (SERM), SRVA reduces the noise level by 9.5 dB, which also shows excellent low-frequency signal recovery ability. Benefiting from its fading suppression, the false alarm of localization is mitigated and the phase recovery can be distortionless. The proposed and verified method is helpful for the application of SDM-based MCF in long-distance distributed fiber sensors and accelerates the progress of integrated sensing and communication.

Distributed optical fiber sensing based on optical frequency domain reflectormeter (OFDR) is a promising technology to achieve a high spatial resolution downwards to several millimeters. To reduce the interaction between the spatial and spectral resolution, a OFDR signal processing method based on Morlet wavelet transform (WT) is proposed to enrich spectrum information especially under a high spatial resolution, and the resolution of spectrum/measured distributed sensing physical quantity can thus be improved. The relationship among distributed sensing parameters and wavelet parameters is demonstrated. And the spectral resolution, spatial interval of the measured gauge and spatial resolution are all manually controllable by adjusting wavelet parameters. To the best knowledge of the authors, it is the first time to report a practical WT method for high performance OFDR. Experimental results indicate that significant improvements, such as strain resolution of 1 le, average repeatability over a full strain range (3000 le) of 4.3 με, and nonlinearity of lower than 0.67 The advantages of this method include high spatial resolution, high spectral resolution, high robustness, and excellent applicability with current OFDR systems.

The spectral purity of fiber lasers has become a critical issue in both optical sensing and communication fields. As a result of ultra-narrow intrinsic linewidth, stimulated thermal Rayleigh scattering (STRS) has presented special potential to compress the linewidth of fiber lasers. To suppress stimulated Brillouin scattering (SBS), the most dominant disturbance for STRS in optical fibers, a semi-quantitative estimation has been established to illuminate the mechanism of suppressing SBS in a periodic tapered fiber, and it agrees with experimental results. Finally, a linewidth compression device based on STRS is integrated into a single-longitudinal-mode ring-cavity fiber laser with secondary cavities, and its linewidth is verified to be 200 Hz through a self-heterodyne detecting and Voigt fitting method.

Focusing on high resolution optical spectroscopy, a coherent optical spectrum analysis (COSA) system is investigated in this paper. Principle is built to demonstrate the operation of COSA and its signal processing in both time and frequency domain. According to COSA principle, resolution bandwidth (RBW) filters are found to have significant influence on power accuracy and spectral resolution of the optical spectrum analysis (OSA). Much effort is paid to design RBW filters, including center frequency, bandwidth and type of filters. Two RBW filters are optimized to reduce the power uncertainty of different spectral resolution and satisfy different signal under test. Then, simulations and experiments are conducted to verify COSA principle and results show that the power uncertainty is less than 0.5% and 1.2% for high and medium spectral resolution application, respectively. Finally, experiments on the OSA of actual spectra indicate that COSA system can achieve a 6 MHz spectral resolution and has an excellent capacity in analysis of fine spectrum structures.

A novel optical frequency domain reflectometer (OFDR) processing algorithm is proposed to enhance the measurable range and data processing rate using a narrow swept spectrum range and reducing the time consuming of the process distributed sensing results. To reduce the swept wavelength range and simultaneously enhance strain measurable range, the local similarity characteristics of Rayleigh scattering fingerprint spectrum is discovered and a new similarity evaluation function based on least-square method is built to improve the data processing rate and sensing performance. By this method, the strain measurable range is raised to 3000 µε under a highest spatial resolution of 3 mm when the swept spectrum range is only 10 nm and the data processing rate is improved by at least 10 times. Experimental results indicate that a nonlinearity of less than 0.5%, a strain resolution of better than 10 µε, a repeatability at zero strain of below ±0.4 GHz and a full-scale accuracy is lower than 0.85 GHz under a highest spatial resolution of 3 mm can be achieved. Advantages of this method are fast processing rate, large strain measurable range, high SNR, and applicability with current OFDR systems.