Distributed fiber acoustic sensing (DAS) technology can continuously spatially detect disturbances along the sensing fiber over long distance in real time. It has many unique advantages, including, large coverage, high time-and-space resolution, convenient implementation, strong environment adaptability, etc. Nowadays, DAS becomes a versatile technology in many fields, such as, intrusion detection, railway transportation, seismology, structure health monitoring, etc. In this paper, the sensing principle and some common performance indexes are introduced, and a brief overview of recent DAS researches in Shanghai Institute of Optics and Fine Mechanics (SIOM) is presented. Some representative research advances are explained, including, quantitative demodulation, interference fading suppression, frequency response boost, high spatial resolution, and distributed multi-dimension localization. The engineering applications of DAS, carried out by SIOM and other groups, are summarized and reviewed. Finally, possible future directions are discussed and concluded. It is believed that, DAS has great development potential and application prospect.

Phase-demodulated phase-sensitive time domain reflectometer (-OTDR) has attracted much attention because of its linear relationship between the phase variation and the amplitude of the vibration. However, it suffers from limited signal-to-noise ratio (SNR) and signal fading, due to the inherent low Rayleigh scattering coefficient and randomly spatial non-uniform distribution of the refractive index. Here, a -OTDR system based on wavelength diversity is demonstrated, which can enhance the SNR and reduce signal fading simultaneously by using differential vector aggregation method. A theoretical model is built, and the linear relationship between SNR improvement and diversity scale is analyzed. The verification experiment is conducted, and in the further experiments, the frequency and wavelength diversity technology are cascaded to achieve a diversity scale of 20. After differential vector aggregation method, the external disturbance signal is well reconstructed and the noise floor is reduced by 13.4dB, which is basically consistent with the theoretical analysis.

Distributed fiber acoustic sensing (DAS) technology can measure acoustic waves along long-distance optical fiber with high spatial resolution. Due to its unique advantages, DAS has been applied in wide fields. However, DAS currently still suffers from limited sensitivity and severe signal fading. Due to the inherent random nature and low signal intensity of Rayleigh backscattering, it is a challenge to essentially eliminate these fundamental limitations. Here a DAS system using its distributed sensing feature is demonstrated with dense multichannel signal integration, complete elimination of signal fading and 100-fold improvement of signal-to-noise ratio (SNR) are experimentally demonstrated. These results provide a simple and effective method to improve DAS performance in practical applications. As far as we know, it is the first time that the distributed sensing characteristic is utilized to tackle fading and sensitivity for DAS, simultaneously. It is believed that this method will promote the process of DAS large-scale applications and help DAS to attract widespread attentions, especially in intrusion detection, acoustic emission flaw detection, near-surface dynamics and characterization, etc.

It is a basic task in Brillouin distributed fiber sensors to extract the peak frequency of the scattering spectrum, since the peak frequency shift gives information on the fiber temperature and strain changes. Because of high-level noise, quadratic fitting is often used in the data processing. Formulas of the dependence of the minimum detectable Brillouin frequency shift (BFS) on the signal-to-noise ratio (SNR) and frequency step have been presented in publications, but in different expressions. A detailed deduction of new formulas of BFS variance and its average is given in this paper, showing especially their dependences on the data range used in fitting, including its length and its center respective to the real spectral peak. The theoretical analyses are experimentally verified. It is shown that the center of the data range has a direct impact on the accuracy of the extracted BFS. We propose and demonstrate an iterative fitting method to mitigate such effects and improve the accuracy of BFS measurement. The different expressions of BFS variances presented in previous papers are explained and discussed.

Distributed optical fiber acoustic sensing technology (DAS) based on Rayleigh backscattering (RBS) is experiencing a rapid development because of the unique capability of measuring acoustic waves along long-distance optical fiber with high spatial resolution, that has broad prospects of applications, including geophysical prospecting, seismology, pipeline security, and train tracking. Despite the numerous applications, DAS currently suffers from high noise level and insufficient signal-to-noise ratio (SNR) due to inherent low RBS coefficient (∼ −70 dB/m) in fiber, and cannot meet the application requirements of weak signal detection. Here, an ultra-low-noise MIMO DAS system using few-mode fibers (FMF) is proposed. FMF is characterized by higher non-linear effect threshold and larger capture fraction of RBS light, and through MIMO technology, the system can realize higher diversity scale and obtain more SNR gain. In addition, ‘frequency label’ method is proposed to address the signal aliasing problem in transmission modes. In preliminary experiments, a 4×4 MIMO Φ-OTDR system is realized, where the minimum noise floor is −88 dB rad ² /Hz with corresponding strain resolution of 0.15 $p\varepsilon /\sqrt {Hz} $ . These results pave the way for advanced acoustic applications of DAS, such as acoustic emission and marine acoustics.

Phase-sensitive optical time domain reflectometer (Φ-OTDR) has attracted attention in scientific research and industry because of its distributed dynamic linear response to external disturbances. However, the signal-to-noise ratio (SNR) of Φ-OTDR is still a limited factor by the weak Rayleigh Backscattering coefficient. Here, the multi-transverse modes heterodyne matched-filtering technology is proposed to improve the system SNR. The capture efficiency and nonlinear threshold are increased with multiple transverse modes in few-mode fibers; the incident light energy is permitted to be enlarged by a wider probe pulse by using heterodyne matched-filtering without spatial resolution being deteriorated. As far as we know, this is the first time that both multi-transverse modes integration method and digital heterodyne matched filtering method have been used to improve the SNR of Φ-OTDR simultaneously. Experimental results show that the noise floor is reduced by 11.4 dB, while the target signal is kept. We believe that this proposed method will help DAS find important applications in marine acoustic detection and seismic detection.