Abstract
A unified framework is proposed for analysis and synthesis of spatial sound fields. In the sound field analysis (SFA) phase, an unbaffled 24-element circular microphone array (CMA) is utilized to "encode" the sound field based on the plane-wave decomposition, whereas in the sound field synthesis (SFS) phase a 32-element rectangular loudspeaker array is employed to "decode" the target sound field using pressure matching technique. Depending on the sparsity of the sound sources, the SFA stage can be implemented in two ways. For the sparse-source scenario, a two-stage algorithm is utilized to estimate the source bearings using the minimum power distortionless response (MPDR) and the associated amplitudes of plane waves using the Tikhonov regularization (TIKR) algorithm. Alternatively, a one-stage algorithm based on compressive sensing (CS) algorithm can be used. The SFA technique for the nonsparse-source scenario is useful in establishing the room response model, as required in the pressure matching step of the SFS phase. Three SFS approaches with optimal regularization parameters are compared in terms of localization performance and audio quality. The integrated acoustic array system is validated with localization performance. Experimental results are presented.