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A Estimation of Signal-to-Interference-Plus-Noise Ratios (SINRs) Exploiting Non-stationarity

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Part of the Lecture Notes in Control and Information Science book series (LNCIS,volume 315)

Abstract

Our discussion about optimum data-dependent beamforming has shown that the second-order statistics of the sensor signals w.r.t. the desired signal and w.r.t. interference-plus-noise are required for realizing robust optimum datadependent beamformers. For realizations in the DFT domain, especially, estimates of power spectral densities and of spatio-spectral correlation matrices w.r.t. the desired signal and w.r.t. interference-pl us-noise are necessary. Consider, e.g., the optimum MMSE beamformer in the DTFT domain after (4.110) that requires the PSD and the spatio-spectral c orrelation matrix of interference-plus-noise. Such estimates can be obtained with, e.g., the minimum statistics after [Mar01a] using the generalization of [Bit02] for estimating spatio-spectral correlation matrices w.r.t. interference-plus-noise. However, these methods assume a slowly time-varying PSD of i nterference-plus-noise relative to a strongly time-varying PSD of the desired signal.

Keywords

  • Sensor Signal
  • Spatial Coherence
  • Block Time
  • Wideband Signal
  • Array Gain

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/11311942_9
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Herbordt, W. A Estimation of Signal-to-Interference-Plus-Noise Ratios (SINRs) Exploiting Non-stationarity. In: Sound Capture for Human/Machine Interfaces. Lecture Notes in Control and Information Science, vol 315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11311942_9

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  • DOI: https://doi.org/10.1007/11311942_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23954-3

  • Online ISBN: 978-3-540-31592-6

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