In this thesis, a computationally efficient method for detecting a whistle and capturing it using a 4 microphone array is proposed. Furthermore, methods are developed to efficiently process the data captured from all the microphones to estimate the direction of the sound source. The accuracy, the shortcoming and the constraints of the method proposed are also discussed. There is an emphasis placed on being computationally efficient so that the methods may be implemented on a low cost microcontroller and be used to provide a heading to an Unmanned Ground Vehicle. / MS / As humans, we rely on our sense of hearing to help us interact with the outside world. It helps us to listen not just to other people but also for sounds that maybe a warning for us. It can often be the first warning we get of an impending danger as we might hear a predator before we see it or we might hear a car brake and slip before we turn to look at it. However, it is not merely the ability to hear a sound that makes hearing so useful. It is the fact that we can tell which direction the sound is coming from that makes it so important. That is what allows us to know which direction to turn towards to respond to someone or from which direction the sound warning us of danger is coming. We may not be able to pinpoint the location of the source with complete accuracy but we can discern the general heading. It was this idea that inspired this research work. We wanted to be capable of estimating where a sound is coming from while being computationally efficient so that it may be implemented in real time with the help of a low cost microcontroller. This would then be used to provide a heading to an Unmanned Ground Vehicle while keeping the costs down.