Regularization using Monte Carlo simulation to make optimal beamformers robust to system perturbations.

@article{Bai2014RegularizationUM,
  title={Regularization using Monte Carlo simulation to make optimal beamformers robust to system perturbations.},
  author={Mingsian Robin Bai and Ching-Cheng Chen},
  journal={The Journal of the Acoustical Society of America},
  year={2014},
  volume={135 5},
  pages={2808-20}
}
Design of optimal beamformers that withstand system perturbations such as channel mismatch, sensor position error, and pointing error has been a key issue in real-world applications of arrays. This paper aims to characterize the array performance in relation to the random perturbations from a statistical perspective. In the synthesis stage, directivity index and front-to-back ratio are employed as the performance measures for beamformer optimization. Filter coefficients of the arrays are… CONTINUE READING