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Tracking of multidimensional TDOA for multiple sources with distributed microphone pairs

机译：使用分布式麦克风对跟踪多个来源的多维TDOA

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摘要

This paper presents a general framework for tracking the time differences of arrivals of multiple acoustic sources recorded by distributed microphone pairs. Tracking is based on a three-stage analysis. Complex-valued propagation models are extracted at different time instants and frequencies using either the independent component analysis or the phase of the cross-power spectrum evaluated at each microphone pair. In both cases, approximated densities of the propagation time delays are derived through the generalized state coherence transform. A sequential Bayesian tracking scheme with an integrated activity detection is finally implemented through disjoint particle filters based on a track-before-detect strategy. Experiments on both synthetic and real data recorded by two distributed microphone pairs show that the proposed framework can detect and track up to five sources simultaneously active in a reverberant environment.
机译：本文提出了一个通用的框架，用于跟踪由分布式麦克风对记录的多个声源到达的时间差。跟踪基于三阶段分析。使用独立分量分析或在每个麦克风对评估的交叉功率谱的相位，可以在不同的时间和频率上提取复数值传播模型。在两种情况下，传播时间延迟的近似密度都是通过广义状态相干变换得出的。最后，基于检测前跟踪策略的不相交粒子滤波器实现了具有集成活动检测的顺序贝叶斯跟踪方案。由两个分布式麦克风对记录的合成和真实数据的实验表明，所提出的框架可以检测并跟踪多达五个在混响环境中同时活跃的声源。

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