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Localization of multiple acoustic sources with small arrays using a coherence test

机译:使用相干测试对具有小阵列的多个声源进行定位

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摘要

Direction finding of more sources than sensors is appealing in situations with small sensor arrays. Potential applications include surveillance, teleconferencing, and auditory scene analysis for hearing aids. A new technique for time-frequency-sparse sources, such as speech and vehicle sounds, uses a coherence test to identify low-rank time-frequency bins. These low-rank bins are processed in one of two ways: (1) narrowband spatial spectrum estimation at each bin followed by summation of directional spectra across time and frequency or (2) clustering low-rank covariance matrices, averaging covariance matrices within clusters, and narrowband spatial spectrum estimation of each cluster. Experimental results with omnidirectional microphones and colocated directional microphones demonstrate the algorithm’s ability to localize 3–5 simultaneous speech sources over 4 s with 2–3 microphones to less than 1 degree of error, and the ability to localize simultaneously two moving military vehicles and small arms gunfire.
机译:在传感器阵列较小的情况下,寻找比传感器更多的源的方向很有吸引力。潜在的应用包括助听器的监视,电话会议和听觉场景分析。一种用于时频稀疏源(例如语音和车辆声音)的新技术使用相干性测试来识别低阶时频箱。这些低秩的bin可以通过以下两种方式之一进行处理:(1)在每个bin上进行窄带空间频谱估计,然后对时间和频率上的定向频谱求和,或(2)聚类低秩的协方差矩阵,对集群内的协方差矩阵求平均,每个集群的窄带空间频谱估计。使用全向麦克风和并置定向麦克风的实验结果表明,该算法能够使用2–3个麦克风在4 s内将3-5个同时语音源定位到小于1度的误差,并且能够同时定位两辆移动军车和小型武器炮火。

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