Speaker
Description
Distributed acoustic sensing (DAS) based on phase-sensitive optical time-domain reflectometry enables optical fibers to operate as dense underwater acoustic arrays with large aperture and continuous spatial sampling. This capability creates new opportunities for wide-area underwater acoustic monitoring and target detection. Nevertheless, applying conventional array signal processing techniques to DAS measurements remains challenging in practical underwater environments. Existing approaches based on covariance fitting or subspace direction-of-arrival estimation rely heavily on accurate array manifold modeling and often require prior knowledge of the source-to-array distance in near-field scenarios. In distributed fiber sensing systems, array geometry mismatch, environmental variability, and uncertainty in range information can significantly degrade localization performance, particularly for coherent acoustic sources. To address these challenges, this paper proposes a fast super-resolution acoustic imaging method for underwater DAS arrays based on improved Richardson–Lucy (RL) deconvolution. DAS signals are first processed using delay-and-sum beamforming to generate conventional acoustic images, after which RL iterative deconvolution reconstructs the spatial distribution of acoustic sources. To handle the large data volume of DAS systems, a spatial-resampling-based fast RL deconvolution method is developed to significantly reduce computational complexity while preserving spatial resolution. Tank experiments conducted at Harbin Engineering University and lake experiments in Danjiangkou using real DAS data demonstrate that the proposed approach can resolve coherent near-field acoustic sources with super-Rayleigh resolution, while reducing the mainlobe width by approximately 60%, suppressing sidelobe levels by more than 10dB, and achieving range estimation errors below 0.2m. These results demonstrate that the proposed fast RL-based imaging approach provides an efficient and robust solution for high-resolution underwater acoustic sensing using DAS arrays.