Directional Acoustic Source´S Position and Orientation Estimation Approach by a Microphone Array Network

In this paper we present a directional acoustic source´s position and orientation estimation approach by a microphone array network in an enclose environment. In this work we assumed that at least one array in the network yields an acceptable position estimation, and based on this assumption we try to automatically select this array and determine the source´s orientation. Here, position estimates are determined indirectly using time delay of arrival (TDOA) from microphone pairs. A position candidate and energy related features (power level of the recorded signals and correlation value between pairs of recorded signals) were determined a priori for each array, and used as input of an artificial neural network (ANN) whose outputs are the orientation and the array which has the most likely source´s position. Additionally, we derive weighting functions based on the ANN output and use them to combine array estimates to obtain a more reliable position estimation.