Localization of an acoustic source by using algorithms that estimate the direction from which the acoustic signal is coming from, helps to address a long time hands-free communications challenge. Applications such as video conferencing, robot processing, hands-free communications, etc require a robust algorithm that accurately locates the Direction of Arrival of incoming wave-fronts with high precision. The steered response power with phase alignment transform method (SRP-PHAT) is a robust localization algorithm. However, the algorithm faces high computation complexity, making it unsuitable for real time applications. Constraining the search space proposed in this thesis found to improve performance of the proposed algorithm. This thesis implements SRP-PHAT algorithms at the biometric lab at Blekinge Institute of Technology and evaluates its performance and the accuracy. Implementation is done in both 2D and 3D for both white noise and speech signal by using linear and square microphone arrays for beamforming. Results presented in this report show that constraining the search space improves the performance of the localization method in terms of computation complexity and the estimation accuracy.