Fast and High-Resolution Acoustic Imaging Localization Method With Fiber-Optic Fabry–Pérot Sensor Array

An improved deconvolution beamforming algorithm is put forward for acoustic imaging localization employing a fiber optic Fabry-Pérot (FP) sensor array. In this method, an adaptive step-size fast iterative shrinkage-thresholding algorithm (AFISTA) is incorporated into the DAMAS2 framework to expedite the solution process. Additionally, the Richardson-Lucy (RL) algorithm is applied to enhance the spatial resolution of imaging. Simulation results reveal that, after 15 iterations, a half power beamwidth (HPBW) of 0.051 m is achieved by the proposed algorithm, with the computation time being merely 2.60 s, approximately half of that required by the conventional algorithm. Experimental results indicate that, with the same number of iterations, an HPBW of 0.079 m is attained, and the computation time is 3.55 s. These results demonstrate that the proposed algorithm not only improves computational efficiency but also enhances imaging spatial resolution, thus rendering it well-suited for acoustic imaging localization in complex environments using a fiber-optic FP sensor array.