Clustering based multi-object positioning system

Acoustic source positioning plays an important role in military tracking unwelcome objects. A system for this application must be capable of dealing with the input recorded convolved mixture signals while minimizing the high communication and computation cost. This paper describes a distributed system for positioning multiple independent moving sources relying on acoustic signals. The sensors pre-process the sensed data to obtain the frequency features before compressing and sending it to the base. At the base, the source positioning are carried out via two clustering stages and an optimization method. Analysis and simulation results show that our system provides high accuracy and needs neither much communication nor complex computation in a distributed manner. It is robust even when there exists high noise with Rayleigh multi-path fading under Doppler effect and when the number of independent sources is greater than the microphone number.