Li Hao, Fan Cunzheng, Shi Zhengxuan, Yan Baoqiang, Chen Junfeng, Yan Zhijun, Liu Deming, Shum Perry, Sun Qizhen
Opt Express. 2022 Aug 1;30(16):29639-29654. doi: 10.1364/OE.455747.
In order to suppress the noise of the coherent fiber distributed acoustic sensing (DAS) system, the spatio-temporal joint oversampling-downsampling technique is proposed. The spatial oversampling is used for artificially dense sampling, whose spacing is far less than the target spatial resolution. Then the spatial downsampling performed by the average of multiple differential sub-vectors is utilized to reduce the influence of noise vectors, which could completely eliminate the interfere fading without increasing any system complexity and introducing any crosstalk. Meanwhile, the temporal oversampling-downsampling is analyzed from the perspective of theory and simulation, demonstrating that the noise floor will decrease with the increase of downsampling coefficient. The temporal oversampling is carried out to expand the noise distribution bandwidth and ensure the correct quantization of the noise frequency. Then the temporal downsampling of differential phase reconstruction is utilized to recover the target bandwidth and reduce the out-of-band noise. The experimental results prove that the noise floor is inversely correlated with the spatiotemporal downsampling factors. The strain resolution of the DAS system with the proposed scheme can reach 2.58pε/√Hz@100Hz-500Hz and 9.47pε/√Hz@10Hz under the condition of DC-500Hz target bandwidth, as well as the probability of the large-noise sensing channels is greatly reduced from 44.32% to 0%. Moreover, the demodulated SNR of dynamic signal is improved by 20.8dB compared with the traditional method. Without any crosstalk, the noise floor is optimized 8dB lower than the averaging technique. Based on the proposed method, the high-performance DAS system has significant competitiveness in the applications with the demand of high-precision and high-sensitivity, such as passive-source seismic imaging and VSP exploration.
为了抑制相干光纤分布式声学传感(DAS)系统的噪声,提出了时空联合过采样-降采样技术。空间过采样用于人工密集采样,其间距远小于目标空间分辨率。然后利用多个差分子向量平均进行的空间降采样来降低噪声向量的影响,这可以在不增加任何系统复杂度和引入任何串扰的情况下完全消除干扰衰落。同时,从理论和仿真角度分析了时间过采样-降采样,结果表明噪声基底会随着降采样系数的增加而降低。进行时间过采样以扩展噪声分布带宽并确保噪声频率的正确量化。然后利用差分相位重构的时间降采样来恢复目标带宽并降低带外噪声。实验结果证明,噪声基底与时空降采样因子呈负相关。在所提方案下,DAS系统在直流-500Hz目标带宽条件下,100Hz - 500Hz时应变分辨率可达2.58pε/√Hz,10Hz时可达9.47pε/√Hz,同时大噪声传感通道的概率从44.32%大幅降低至0%。此外,与传统方法相比,动态信号的解调信噪比提高了20.8dB。在无任何串扰的情况下,噪声基底比平均技术优化低8dB。基于所提方法,高性能DAS系统在无源地震成像和VSP勘探等高精度、高灵敏度需求的应用中具有显著竞争力。