We have experimentally analyzed and compared the performance of optical frequency domain reflectometry (OFDR) assisted by image processing methods including wavelet transform and Gaussian filter arithmetic in terms of strain measurement range. The incomplete space similarity in the distributed strain measurement is used to recover the accurate strain gradient information by the image processing methods. The distributed spectrum shifts of the cross-correlation calculation along the sensing fiber between reference signal and measurement signal is regarded as a two-dimension (2D) image which is disposed by the proposed methods rather than extracting the spectrum shifts immediately. Compared with the traditional processing method, the proposed image processing method is able to remove and smoothen the fake peaks or outliers caused by the spatial mismatch of stretched fiber in OFDR system. In the experiments, strain gradient information up to 7000 μϵ can be identified by the proposed methods with a 4 mm spatial resolution. Furthermore, the wavelet transform is discussed in detail in order to determine the value of the suitable decomposition level in OFDR data processing scheme. The proposed methods provide a new idea to achieve the wide strain measurement range in OFDR system, which is a significant step toward a high-performance distributed sensing system, especially for occasions when a wide range of strain measurement is required.

Measurement accuracy of the optical frequency domain reflectometry (OFDR) will be deteriorated severely when the spatial resolution is improved due to the influence of the random noise, especially in long range distributed fiber optical sensing system. In order to eliminate the random noise, we have experimentally compared and analyzed the performance of OFDR system with and without the image processing methods in term of spatial resolution. The data arrays of the cross-correlation results are obtained after processing the collected distributed Rayleigh scattering signals along the sensing fiber, which can be used to construct a two-dimension (2D) image with the spectrum shift information induced by the strain. Thus, the image denoising methods can be applied to remove the random noise and improve the measurement accuracy. Based on this principle, two image denoising methods including the total variation method and the 2D Gaussian filter arithmetic are introduced to realize distributed sensing with high spatial resolution in long distance OFDR system. Experimental results show that the random noise can be suppressed and the outliers can be removed by the proposed methods. The strain gradients with high spatial resolution are identified effectively when the image denoising methods are used. Furthermore, spatial resolution with 1.3mm is achieved by the proposed methods with a wavelength sweeping rate of 20nm/s in 52m sensing fiber. The proposed methods provide a potential solution for OFDR system in long distance sensing with high spatial resolution, which is a significant step toward a high-performance OFDR system for practical applications.

Information sensor can realize the ubiquitous connection between objects and humans by the distributed fiber-optic sensor array, i.e., emerging infrastructure for Internet of Things, in which optical frequency domain reflectometry (OFDR) with its high spatial resolution plays an important role in achieving intelligent perception and identification of the objects. However, given a certain fiber length, there are tradeoffs among the processing speed, the spatial resolution, and the strain measurement range. In this article, a time optimization interpolation method and a distance domain compensation method are reported and experimentally verified to break the aforementioned tradeoffs for the first time. First, a full theoretical analysis on how to reduce the interpolation number and the reason why it is difficult to achieve high spatial resolution and large strain measurement and how to resolve it is made. Second in the proof-of-concept experiment, measurements of large strains up to 10 000 $\boldsymbol{\mu } \boldsymbol{\varepsilon }$ are realized along the sensing fiber with a spatial resolution of 2 mm using a conventional OFDR system. Also, the processing time is shortened by 76 times compared with the traditional processing method. This article makes a significant step toward high-performance OFDR system with fast processing, high spatial resolution, and wide strain measurement.

A single-frequency laser based on Yb:YAG crystal-derived silica fiber (YDSF) was demonstrated. The YDSF was fabricated by a molten-core method with a doping concentration of 4.8 wt. % for ${\mathrm{Yb}}_2{\mathrm{O}}_3$, whose gain coefficient and transmission loss were measured to be 1.7 dB/cm and 0.005 dB/cm, respectively. An over 110 mW stable single-frequency laser at 1064 nm was obtained based on a distributed Bragg reflector setup, showing a slope efficiency of 18.5%. The signal-to-noise ratio was $\sim 80\mathrm{dB}$, and the frequency fluctuation was less than 20 MHz within 10 min.

A sub-Nyquist random single-pulse sampling method based compressive sensing technique is proposed firstly to reconstruct signals under test in phase-sensitive optical time domain reflectometry (φ-OTDR). The key information of Rayleigh backscattering curves can be recognized after sparse transformation, which can be successfully reconstructed with far smaller number of measurements by orthogonal matching pursuit algorithm. Unlike the uniform sampling in conventional φ-OTDR system, pulse intervals are randomly modulated to generate a random single-pulse sequence in the proposed method in order to achieve random single-pulse sampling along every sensing point of the fiber. Experimental results verify that pulse sequences with average pulse repetition rate less than 2-kHz can be efficiently utilized to reconstruct an 8-kHz signal under test and obtain its frequency information, as well as to realize the detection of high frequency signals at different locations along the sensing fiber. It is demonstrated that the sampling rate is reduced greatly without any hardware modification compared to that required in the conventional method. This method can break the limits of the traditional Shannon-Nyquist sampling theorem to reconstruct signal, which is of great significance for the sensor performance enhanced in traditional φ-OTDR system.

A photodetector with a commercial quartz tuning fork (QTF) based on photothermal effect was demonstrated. Unlike the commonly used thermosensitive elements, a QTF with the mechanical resonance ability and the piezoelectric effect was used to amplify the photothermal signal. Operating at the optimal operating distance and modulation signal duty ratio selected for the photodetector, the photodetector achieved a good linear response at the wavelength of 1550 nm and 980 nm. And the photoresponsivity of the photodetector reach up to 515 mV/mW at the wavelength of 1550 nm. More important, the detection sensitivity of 0.75 pW at 203 s integration time has been achieved by using the Allan deviation analysis.