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Tracking of multiple moving speakers with multiple microphone arrays

机译:跟踪带有多个麦克风阵列的多个移动扬声器

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In this paper we use multiple microphone arrays to fuse the location estimate from each microphone array which yields an improved estimate of the positions and velocities of multiple, simultaneously active, moving speakers based on time delay of arrivals (TDOAs). Our approach: 1) incorporates kinematic information of moving speakers by using an interacting multiple model (IMM) estimator for each speaker in order to constrain the evolution of the location measurements; 2) fuses the location estimates of the same speaker from multiple microphone arrays for better acoustical coverage of the sensed environment, and 3) directly accounts for the measurement origin uncertainty, i.e., which measurement comes from which speaker by using the probabilistic data association (PDA) technique with the IMM estimator. We demonstrate that a network of arrays combined with the estimation technique widely used in multisensor multitarget tracking area provides a consistent and coherent way to reduce the uncertainty and ambiguity of measurements. The effectiveness of our approach is illustrated by extensive simulation study on tracking a single moving speaker and two closely-spaced speakers with a crossing segment in their trajectories.
机译:在本文中,我们使用多个麦克风阵列融合每个麦克风阵列的位置估计值,从而根据到达时间延迟(TDOA)对多个同时活动的移动扬声器的位置和速度进行改进的估计。我们的方法:1)通过为每个说话者使用交互多模型(IMM)估计器来合并移动说话者的运动学信息,以约束位置测量的演变; 2)将来自多个麦克风阵列的同一扬声器的位置估计融合在一起,以更好地覆盖所感测的环境,并且3)直接考虑测量原点的不确定性,即哪个测量是通过使用概率数据关联(PDA)来自哪个扬声器的)技术与IMM估算器结合使用。我们证明,阵列网络与广泛应用于多传感器多目标跟踪区域的估计技术相结合,提供了一致而连贯的方式来减少测量的不确定性和不确定性。我们的方法的有效性通过广泛的模拟研究得到了证明,该研究跟踪了一个运动的扬声器和两个在轨道上有交叉线段的近距离扬声器。

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