Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics

Part of Advances in Neural Information Processing Systems 12 (NIPS 1999)

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Justinian Rosca, Joseph Ruanaidh, Alexander Jourjine, Scott Rickard


N wideband sources recorded using N closely spaced receivers can feasibly be separated based only on second order statistics when using a physical model of the mixing process. In this case we show that the parameter estimation problem can be essentially reduced to considering directions of arrival and attenuations of each signal. The paper presents two demixing methods operating in the time and frequency domain and experimentally shows that it is always possible to demix signals arriving at different angles. Moreover, one can use spatial cues to solve the channel selection problem and a post-processing Wiener filter to ameliorate the artifacts caused by demixing.