Estimating the position and orientation of an acoustic source with a microphone array network

We propose a method that finds the position and orientation of an acoustic source in an enclosed environment. For each of eight T-shaped arrays forming a microphone array network, the time delay of arrival (TDOA) of signals from microphone pairs, a source position candidate, and energy related features are estimated. These form the input for artificial neural networks (ANNs), the purpose of which is to provide indirectly a more precise position of the source and, additionally, to estimate the source’s orientation using various combinations of the estimated parameters. The best combination of parameters (TDOAs and microphone positions) yields a 21.8% reduction in the mean average position error compared to baselines, and a correct orientation ratio higher than 99.0%. The position estimation baselines include two estimation methods: a TDOAbased method that finds the source position geometrically, and the SRP-PHAT that finds the most likely source position by spatial exploration.