In order to improve the computational efficiency of the classical time-domain rotating source identifier (ROSI) beamforming

two different compression computational grid methods were proposed: one based on conventional beamforming

namely CG2

and the other one obtained from ROSI beamforming with a little amount of sample data

namely CG4. Experimental applications showed that both compression grid methods did not affect the effectiveness of the ROSI algorithm for rotating sound source localization. ROSI beamforming with CG2 can improve the computational efficiency of the ROSI algorithm for rotating sound source localization by a factor of 1 to 2

while ROSI beamforming with CG4 can improve the computational efficiency of the ROSI algorithm for rotating sound source localization by a factor of 13 to 18. In addition

ROSI beamforming with CG4 can still accurately locate the rotating sound source even if the microphone array plane run perpendicular to the rotating sound source plane.