Ultra compression-ratio distributed acoustic sensing system via combination of envelope extraction and compressed sensing

Distributed acoustic sensing (DAS) is experiencing significant growth in applications such as seismological observation, urban cable monitoring, and thunder observation, due to its long sensing distance and high accuracy measurement in distributed sensing. The heterodyne coherent DAS system offers a high-fidelity, linear strain response, but its strain range is limited by the LFM pulse bandwidth. This requires a high-performance gigahertz DAQ, which increases data volume, system cost, and real-time processing challenges. In this work, we propose a data compression scheme for DAS based on envelope extraction hardware and compressed sensing techniques. After compression, the raw data volume is reduced from 9.31 GB/s to 238.42 MB/s for continuous sensing over a 6-km range (80 μ s pulse), achieving a 40-fold reduction. The experiment results show that the compressed data can be effectively reconstructed, and realize strain localization and detection. The proposed compression method mitigates the challenges posed by large raw data volumes and makes the DAS system more applicable to long-duration measurement applications.