Direction of arrival (DOA) estimation from array observations in a noisy environment is discussed. The source amplitudes are assumed to be correlated zero-mean complex Gaussian distributed with unknown covariance matrix. The DOAs and covariance parameters of plane waves are estimated from multi-snapshot sensor array data using sparse Bayesian learning (SBL). The performance of SBL is evaluated in terms of the fidelity of the reconstructed coherency matrix of the estimated plane waves.
|Title of host publication||2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop, SAM 2018|
|Number of pages||5|
|Publication status||Published - 2018|
|Event||10th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2018 - Sheffield, United Kingdom|
Duration: 8 Jul 2018 → 11 Jul 2018
Conference number: 10
|Conference||10th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2018|
|Period||8/07/18 → 11/07/18|
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