High-resolution acoustic beamforming based on genetic algorithms

A beamforming technique based on the genetic algorithm is proposed in this paper. This method reconstructs acoustic sources by exploiting the sparsity. To reduce the computational cost and speed up the implementation, a highly efficient algorithm is further developed by narrowing down the search domain for the genetic algorithm. The performance is numerically investigated through a quantitative analysis of the position and amplitude error of the recovered source, and experimentally demonstrated in acoustic imaging. For this newly established approach, the results indicate a higher resolution capability than the conventional beamforming, and better accuracy and robustness than the compressive sensing beamforming. Overall, the present work can enrich existing high-resolution beamforming methods and benefit relevant acoustic testing applications.