In microphone arrays application,it is difficult to localize sound source accurately and quickly in a noisy and reverberant environment.In order to solve this problem,many researchers have presented different approaches.The steered response power-phase transform weighted(SRP-PHAT) source localization algorithm has been proved robust,however,it requires high computation cost for searching the peak of steered response power in a large location space.Thus,an improved SRP-PHAT method using an orthogonal linear array was presented in this paper,which reduced a two-dimension searching space to a couple of one-dimension ones.Then the parameters of direction of arrival(DOA) were separated,and computed respectively in the one-dimension searching space with coarse-fine strategies of hierarchical search.This algorithm was based on the observation that the wavelengths of the sound from a speech source are comparable to the dimensions of the space being searched and that the source was broadband.A systematic series of comparisons with previous algorithms were made basing on Matlab.Simulations show that the main computational load of SRP-PHAT algorithms has been greatly cut down,and there is no loss in accuracy in the proposed method.The performance of the algorithm can be further improved by using constraints from computer vision.