This paper presents a method for real-time estimation of 2-dimensional direction of arrival (2D-DOA) of one or more sound sources using a nonlinear array of three microphones. 2D-DOA is estimated employing frame-level time difference of arrival (TDOA) measurements. Unlike conventional methods, which infer location parameters from TDOAs using a theoretical model, we propose a more practical approach based on supervised learning. The proposed model employs nearest neighbor search (NNS) applied to a spherical Fibonacci lattice consisting of TDOA to 2D-DOA mappings learned directly in the field. Filtering and clustering post-processors are also introduced for improved source detection and localization robustness.

翻译：本文提出一种采用非线性三麦克风阵列对单个或多个声源进行二维到达方向（2D-DOA）实时估计的方法。该方法利用帧级到达时间差（TDOA）测量值实现二维到达方向估计。与传统方法基于理论模型从TDOA推断位置参数不同，本文提出一种基于监督学习的实用方案。所提模型采用最近邻搜索（NNS）方法，作用于由TDOA到2D-DOA映射构成的球面斐波那契网格（该映射直接在现场学习获得）。为提升声源检测与定位鲁棒性，本文还引入了滤波与聚类后处理模块。