• Infrared and Laser Engineering
  • Vol. 54, Issue 4, 20250097 (2025)
Simeng JIN, Zhisheng YANG, Qing WANG, Yifeng LU..., Xiaobin HONG and Jian WU|Show fewer author(s)
Author Affiliations
  • State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China
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    DOI: 10.3788/IRLA20250097 Cite this Article
    Simeng JIN, Zhisheng YANG, Qing WANG, Yifeng LU, Xiaobin HONG, Jian WU. Research progress on performance evaluation and optimization in Brillouin distributed optical fiber sensing (invited)[J]. Infrared and Laser Engineering, 2025, 54(4): 20250097 Copy Citation Text show less

    Abstract

    Significance Distributed Optical Fiber Sensing (DOFS) plays a crucial role in acquiring spatially distributed environmental data along a sensing fiber, offering superior advantages such as long-range, high-precision, and large-area monitoring. Among various DOFS technologies, Brillouin-based sensing methods—especially Brillouin Optical Time Domain Analyzer (BOTDA) and Brillouin Optical Time Domain Reflectometer (BOTDR)—have become the focus of both academic and industrial research due to their ability to measure temperature and strain along optical fibers with high accuracy. However, the performance of these systems is significantly influenced by their signal-to-noise ratio (SNR), which in turn affects the measurement accuracy, spatial resolution, and dynamic range. Optimizing SNR is therefore critical to improving the overall performance of these systems for practical deployment in fields like civil engineering, energy, aerospace, and infrastructure monitoring.Progress Recent advances in the SNR modeling and system performance optimization of BOTDA and BOTDR systems are reviewed and synthesized. One of the key advancements in recent research is the development of more accurate SNR models that account for various noise sources. These models help quantify the influence of different noise sources and provide guidelines for optimizing system parameters.What’s more, key parameters that affect the system SNR performance, such as pump pulse peak power and probe power in BOTDA systems, are limited by nonlinear effects and difficult to further enhance. In BOTDA systems, the pump pulse peak power typically needs to be adjusted close to the modulation instability (MI) threshold to maximize SNR. Meanwhile, the probe power is mainly constrained by non-local effects and Stimulated Brillouin Scattering (SBS). Extensive researches have focused on this aspect, providing in-depth analysis and proposing advanced solutions to overcome traditional power limitations. Based on SNR modeling, researchers have also developed parameter optimization schemes for BOTDR systems, suggesting that pump pulse peak power and local oscillator (OLO) power need to be reasonably adjusted according to different sensing scenarios to balance optimal performance with lower energy consumption. The careful tuning of these parameters is essential for achieving the best performance in different sensing scenarios, whether it’s for long-distance monitoring or high-precision measurements. Researchers have also proposed optimization criteria for detection and sampling, indicating that the detector bandwidth must be greater than the signal bandwidth to ensure the signal is not distorted, and the sampling rate must be greater than twice the noise bandwidth to avoid noise aliasing. Based on this, applying digital post-processing filtering can achieve optimal denoising effects.In addition to system-level optimization, much progress has been made in post-processing techniques to further enhance the SNR. Digital filtering, signal averaging, and advanced fitting algorithms are now commonly employed to reduce noise and improve the accuracy of the extracted Brillouin frequency shift (BFS). Several studies have demonstrated that high-order signal processing methods, such as wavelet transform and deep learning-based algorithms, can offer additional performance improvements. However, research also suggests that such advanced signal processing methods like image processing and deep learning may not provide significant performance improvements once the system bandwidth and fitting methods have been optimized.Conclusions and Prospects In conclusion, this paper provides a comprehensive overview of the research progress in optimizing the SNR of BOTDA and BOTDR systems, emphasizing the importance of both system-level and post-processing optimizations. By carefully adjusting system parameters, including pump pulse peak power, probe power, and local oscillator power, and employing advanced signal processing techniques, it is possible to approach the performance limits of these classical Brillouin sensing systems. However, while advanced technologies such as distributed amplification and pulse coding show great promise, their complexity and high cost remain barriers to widespread commercialization. Moving forward, further research into low-cost, miniaturized systems that maintain high performance will be critical for the industrialization of Brillouin sensing technology. Additionally, the exploration of higher-order sensing schemes, such as those incorporating advanced amplification and coding techniques, will continue to be a vital research direction, offering new opportunities to push the limits of distributed Brillouin sensing.
    Simeng JIN, Zhisheng YANG, Qing WANG, Yifeng LU, Xiaobin HONG, Jian WU. Research progress on performance evaluation and optimization in Brillouin distributed optical fiber sensing (invited)[J]. Infrared and Laser Engineering, 2025, 54(4): 20250097
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