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基于压缩感知的基于比较器的超低采样率Φ-OTDR系统的信噪比增强

SNR Enhancement for Comparator-Based Ultra-Low-Sampling Φ-OTDR System Using Compressed Sensing.

作者信息

Xiao Zhenyu, Li Xiaoming, Zhang Haofei, Yuan Xueguang, Zhang Yang-An, Zhang Yuan, Li Zhengyang, Wang Qi, Huang Yongqing

机构信息

State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China.

School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.

出版信息

Sensors (Basel). 2024 May 21;24(11):3279. doi: 10.3390/s24113279.

Abstract

The large amount of sampled data in coherent phase-sensitive optical time-domain reflectometry (Φ-OTDR) brings heavy data transmission, processing, and storage burdens. By using the comparator combined with undersampling, we achieve simultaneous reduction of sampling rate and sampling resolution in hardware, thus greatly decreasing the sampled data volume. But this way will inevitably cause the deterioration of detection signal-to-noise ratio (SNR) due to the quantization noise's dramatic increase. To address this problem, denoising the demodulated phase signals using compressed sensing, which exploits the sparsity of spectrally sparse vibration, is proposed, thereby effectively enhancing the detection SNR. In experiments, the comparator with a sampling parameter of 62.5 MS/s and 1 bit successfully captures the 80 MHz beat signal, where the sampled data volume per second is only 7.45 MB. Then, when the piezoelectric transducer's driving voltage is 1 Vpp, 300 mVpp, and 100 mVpp respectively, the SNRs of the reconstructed 200 Hz sinusoidal signals are respectively enhanced by 23.7 dB, 26.1 dB, and 28.7 dB by using compressed sensing. Moreover, multi-frequency vibrations can also be accurately reconstructed with a high SNR. Therefore, the proposed technique can effectively enhance the system's performance while greatly reducing its hardware burden.

摘要

相干相敏光时域反射仪(Φ-OTDR)中大量的采样数据带来了沉重的数据传输、处理和存储负担。通过使用比较器结合欠采样,我们在硬件上实现了采样率和采样分辨率的同时降低,从而大大减少了采样数据量。但这种方式不可避免地会由于量化噪声的急剧增加而导致检测信噪比(SNR)恶化。为了解决这个问题,提出了利用频谱稀疏振动的稀疏性,通过压缩感知对解调后的相位信号进行去噪,从而有效提高检测信噪比。在实验中,采样参数为62.5 MS/s和1位的比较器成功捕获了80 MHz拍频信号,每秒的采样数据量仅为7.45 MB。然后,当压电换能器的驱动电压分别为1 Vpp、300 mVpp和100 mVpp时,使用压缩感知重建的200 Hz正弦信号的信噪比分别提高了23.7 dB、26.1 dB和28.7 dB。此外,多频振动也能以高信噪比准确重建。因此,所提出的技术可以在大大减轻硬件负担的同时有效提高系统性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e4c/11174477/2ce2a1609df9/sensors-24-03279-g001.jpg

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