基于涡旋声波的二维角域高分辨成像方法OA

To address the heavy reliance of conventional back-projection methods on high-order orbital an-gular momentum(OAM)modes in two-dimensional angular-domain imaging with acoustic vortex waves,a high-resolution reconstruction method based on sparse Bayesian learning(SBL)is proposed.Based on an exist-ing multiple-input single-output echo model for acoustic OAM waves generated by a uniform circular ar-ray,the correlation function between adjacent scatterers is analyzed,and the relationship among elevation resolution,array aperture,and target elevation angle is derived.Furthermore,a multi-frequency and multi-mode joint observation model is then constructed to reconstruct the equivalent scattering coefficients in the two-dimen-sional angular domain,and a statistical thresholding strategy is incorporated to improve robustness under noisy con-ditions.Simulation results show that the variation in the mainlobe width of the point spread function is consistent with the theoretical analysis.In a four-point scattering target scenario,the SBL based method can effectively dis-tinguish the targets with an OAM mode range of[-10,10],whereas the conventional back-projection method requires an extended range of[-100,100]to yield comparably clear results.At a signal-to-noise ratio of 13 dB,the enhanced SBL method exhibits more stable reconstruction performance than conventional SBL.These results indicate that the proposed method can improve the resolution of two-dimensional angular-domain imaging using acoustic vortex waves even with a limited-mode conditions.