Robust adaptive beamforming based on interference covariance matrix sparse reconstruction

@article{Gu2014RobustAB,
  title={Robust adaptive beamforming based on interference covariance matrix sparse reconstruction},
  author={Yujie Gu and Nathan A. Goodman and Shaohua Hong and Yu Li},
  journal={Signal Processing},
  year={2014},
  volume={96},
  pages={375-381}
}
Adaptive beamformers are sensitive to model mismatch, especially when the desired signal is present in the training data. In this paper, we reconstruct the interference-plus-noise covariance matrix in a sparse way, instead of searching for an optimal diagonal loading factor for the sample covariance matrix. Using sparsity, the interference covariance matrix can be reconstructed as a weighted sum of the outer products of the interference steering vectors, the coefficients of which can be… CONTINUE READING

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