We propose and experimentally demonstrate a scheme for accelerated fast BOTDA. The effect of signal-to-noise ratio (SNR) on recovery performance of compressed sensing is simulated and analyzed, it is found that a reduction in SNR requires much larger frequency data to recover the original Brillouin gain spectrum (BGS). To enable a high recovery probability, Block-Matching and 3D filtering (BM3D) algorithm is employed to enhance the SNR of Brillouin time trace and reduce the number of averages. Combining with a principal component analysis (PCA) based compressed sensing technique, the Brillouin gain spectrum (BGS) can be successfully reconstructed from only 37.5% frequency data. In the experiment, 75 randomly selected frequency data is acquired to reconstruct the BGS. Distributed strain sensing is achieved over 15 km single-mode fiber with 3 m spatial resolution and 0.52 MHz Brillouin frequency shift (BFS) uncertainty. Due to the accelerated process, the measurement time with 40 averages is less than 0.5 s.

中文翻译：

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压缩感知和图像去噪辅助的加速快速 BOTDA


我们提出并实验演示了一种加速快速 BOTDA 的方案。仿真分析了信噪比（SNR）对压缩感知恢复性能的影响，发现信噪比的降低需要更大的频率数据来恢复原始布里渊增益谱（BGS）。为了实现高恢复概率，采用块匹配和3D滤波（BM3D）算法来增强布里渊时间轨迹的SNR并减少平均次数。结合基于主成分分析 (PCA) 的压缩感知技术，仅从 37.5% 的频率数据即可成功重建布里渊增益谱 (BGS)。在实验中，随机选择75个频率数据来重建BGS。分布式应变传感是在 15 km 单模光纤上实现的，具有 3 m 空间分辨率和 0.52 MHz 布里渊频移 (BFS) 不确定性。由于过程加速，40次平均值的测量时间小于0.5秒。