Application of Bayesian Regularization Criterion in near Field Acoustic Holography Based on Equivalent Source Method

Abstract

In order to choose an optimal regularization parameter for near field acoustic holography (NAH) based on equivalent source method (ESM), Bayesian regularization criterion method was introduced to solve the inverse problem. Comparison simulations were conducted with generalized cross validation method (GCV), L-curve method and Hald regularization formula method at various sound source frequencies, hologram distances, and Signal-to-Noise Ratios (SNR). The results show that GCV, L-curve, and Hald regularization formula method cannot achieve the optimal regularization parameter at large hologram distances, high noise levels, high frequencies and input SNR errors. However, Bayesian regularization criterion method is not affected by these restrictions and has excellent reconstruction performance in wide frequency band. Further experiment validates the correctness and effectiveness of the application of Bayesian regularization criterion method in ESM-based NAH, thus providing a new guidance for the solving of inverse problem in ESM-based NAH.