A Robust and Low-Complexity Source Localization Algorithm for Asynchronous Distributed Microphone Networks

In this paper, we propose a robust and low-complexity acoustic source localization technique based on time differences of arrival (TDOA), which addresses the scenario of distributed sensor networks in 3D environments. Network nodes are assumed to be unsynchronized, i.e., TDOAs between microphones belonging to different nodes are not available. We begin with showing how to select feasible TDOAs for each sensor node, exploiting both geometrical considerations and a characterization of the overall generalized cross correlation (GCC) shape. We then show how to localize sources in the space-range reference frame, where TDOA measurements have a clear geometrical interpretation that can be fruitfully used in the scenario of unsynchronized sensors. In this framework, in fact, the source corresponds to the apex of a hypercone passing through points described by the sole microphone positions and TDOA measurements. The localization problem is therefore approached as a hypercone fitting problem. Finally, in order to improve the robustness of the estimate, we include an outlier detection procedure based on the evaluation of the hypercone fitting residuals. A refinement of source location estimate is then performed ignoring the contributions coming from outlier measurements. A set of simulations shows the performance of individual blocks of the system, with particular focus on the effect of TDOA selection on source localization and refinement steps. Experiments on real data validate the localization algorithm in an everyday scenario, proving that good accuracy can be obtained while saving computational cost in comparison with state-of-the-art techniques.