Distributed optical fiber sensors (DOFS) offer unprecedented features, the most unique one of which is the ability of monitoring variations of the physical and chemical parameters with spatial continuity along the fiber. Among all these distributed sensing techniques, optical frequency domain reflectometry (OFDR) has been given tremendous attention because of its high spatial resolution and large dynamic range. In addition, DOFS based on OFDR have been used to sense many parameters. In this review, we will survey the key technologies for improving sensing range, spatial resolution and sensing performance in DOFS based on OFDR. We also introduce the sensing mechanisms and the applications of DOFS based on OFDR including strain, stress, vibration, temperature, 3D shape, flow, refractive index, magnetic field, radiation, gas and so on.

In unmanned monitoring such as perimeter security, pipeline detection, railway security, and so on, it is still a challenging task to accurately locate the irregular vibration events. Compared with traditional vibration detection technologies, distributed optical fiber vibration sensors (DOFVSs) have superior advantages such as high spatial resolution, large monitoring range, good concealment, excellent flexibility, and simple sensing structure. The DOFVS can be mainly classified into two types, i.e., the interferometer-based DOFVS (IDOFVS) and the backscattering-based DOFVS (BDOFVS). In particular, IDOFVS has unique sensing advantages, such as high stability, simple structure, high sensitivity, and wide frequency response. In this article, the development of long-distance IDOFVS in recent years has been summarized. The sensing principle of IDOFVS has been theoretically explained. The specific classification of the IDOFVS and the corresponding sensing structures are described in detail. In addition, the long-distance distributed vibration sensing structure and processing algorithms, such as denoising and locating algorithms, are analyzed. Finally, the performance of recent long-distance IDOFVS has been compared and the development direction has been discussed.

We present a novel distributed high sensitivity static strain sensing method based on differential relative phase in optical frequency domain reflectometry (OFDR). By performing two separate tests of the measurement and the reference states, distributed strain sensing can be achieved by acquiring differential relative phase between these two states, which can reduce common-mode residual nonlinear phase in OFDR greatly and favor phase unwrapping, thanks to decreasing wrapped phase change rate as a function of the length of fiber under test (FUT). In addition, an all grating optical fiber that has a stronger backscattering than that of a standard single-mode fiber is used as FUT in the presented OFDR system. In the experiment, the measurement range of static strain variation is 0 to 25 με, the sensing spatial resolution is 4.35 cm, and the minimum measurable strain variation is 0.25 με along with a total 36 m FUT. Compared with the widely-used Rayleigh backscattering spectra shift cross-correlation method using the same data, the presented method can provide a better sensing performance of measuring a minor strain variation under the same sensing spatial resolution.

Optical frequency domain reflectometry (OFDR) offers a unique combination of ultra-high spatial resolution and sensitivity, which makes OFDR became one of the most rapidly developing fields of distributed optical fiber sensing, especially in three-dimensional (3D) shape sensing, acoustic sensing, dynamic strain sensing and refractive index sensing besides temperature and static strain. In this review, we covered key technological developments and insights of OFDR in recent years, which includes nonlinear tuning correction, fast spectrum analysis, Rayleigh backscattering spectra demodulation, Rayleigh scattering enhancement fiber, phase based demodulation, high temperature sensing, dynamic strain sensing, acoustic sensing, 3D shape sensing, refractive index sensing, biochemical sensing, polarimetric OFDR sensing and photonic integrated circuits based OFDR. Finally, we presented challenges and prospects of distributed optical fiber sensing based on OFDR.

We use a spectrum interpolation technique to improve the distributed strain measurement accuracy in a Rayleigh-scatter-based optical frequency domain reflectometry sensing system. We demonstrate that strain accuracy is not limited by the “uncertainty principle” that exists in the time–frequency analysis. Different interpolation methods are investigated and used to improve the accuracy of peak position of the cross-correlation and, therefore, improve the accuracy of the strain. Interpolation implemented by padding zeros on one side of the windowed data in the spatial domain, before the inverse fast Fourier transform, is found to have the best accuracy. Using this method, the strain accuracy and resolution are both improved without decreasing the spatial resolution. The strain of 3 μϵ within the spatial resolution of 1 cm at the position of 21.4 m is distinguished, and the measurement uncertainty is 3.3 μϵ.

A phase demodulation method for quasi-distributed acoustic sensing (DAS) systems based on a dual-identical-chirped-pulse and weak fiber Bragg gratings (WFBGs) is proposed. Compared to the use of Rayleigh backscattering light in optical fibers, the implementation of WFBGs can contribute to obtaining an optical signal with a higher signal-to-noise ratio (SNR). The dual-identical-chirped-pulse is generated by a time-delay fiber, and the sinusoidal carrier is generated by the interference between the two chirped pulses reflected by adjacent WFBGs. The phase of the sinusoidal carrier represents the dynamic strain change posed on the sensing fiber. Discrete Fourier transform is used to directly retrieve the phase information. The performance of the phase demodulation from interference signals under different sinusoidal carrier frequencies and SNRs is numerically investigated. The piezoelectric transducer is employed to emulate the sound in the experiment to verify the effectiveness of our method. It is shown that the dynamic strain can be well reconstructed at the end of a 101.64 km fiber when the signal SNR is down to 3.234 dB. Our proposed method enables the application of the long-distance sensing in quasi-DAS systems.