采用稀疏测量的高分辨率相干声场分离

现有相干声场分离方法受限于采样定理,要获取高分辨率的分离结果需要大量的测点。为降低测量成本,提出一种采用稀疏测量的高分辨率相干声场分离方法。该方法首先根据波叠加原理构建传递矩阵,然后通过奇异值分解技术获取声场的一组稀疏正交基,最后利用稀疏正则化获取权重系数的稀疏解并将其用于分离目标声场。仿真和实验结果表明:在测点数较少的情况下,该方法相较于常规等效源声场分离方法的分离精度更高。同时,常规等效源声场分离方法的分离结果分辨率受限于测点数目,而该方法可以在测点数较少情况下实现高分辨率的相干声场分离。 

High-resolution separation of coherent sound field with sparse measurements

The sound field separation method has been widely used for recovering the target sound field in the mixed sound field.However,the methods bear heavy measurement load due to the restriction of sampling theorem.In this study,a sound field separation method was proposed based on compressive sensing.The method consists in representing the sound field in a sparse basis by using the singular value decomposition,and utilizing the sparse regularization to find a sparse solution.The method is validated by both numerical and physical experiments.Comparing to the traditional equivalent source method-based separation,the proposed method has the advantages both on the accuracy and the spatial resolution for under-sampled pressure data.