Automatic estimation of position and orientation of an acoustic source by a microphone array network

Abstract

A method which automatically provides the position and orientation of a directional acoustic source in an enclosed environment is proposed. In this method, different combinations of the estimated parameters from the received signals and the microphone positions of each array are used as inputs to the artificial neural network (ANN). The estimated parameters are composed of time delay estimates (TDEs), source position estimates, distance estimates, and energy features. The outputs of the ANN are the source orientation (one out of four possible orientations shifted by 90 degrees and either the best array which is defined as the nearest to the source) or the source position in two dimensional/three dimensional (2D/3D) space. This paper studies the position and orientation estimation performances of the ANN for different input/output combinations (and different numbers of hidden units). The best combination of parameters (TDEs and microphone positions) yields 21.8% reduction in the average position error compared to the following baselines and a correct orientation ratio greater than 99%. Position localization baselines consist of a time delay of arrival based method with an average position error of 34.1 cm and the steered response power with phase transform method with an average position error of 29.8 cm in 3D space.