354 / 2020-01-13 08:00:00
Single-Snapshot Beamforming using Fast Iterative Adaptive Techniques
Single-snapshot beamforming; Adaptive beamforming; Fast iterative interpolated beamforming; FIIB; SINR; covariance matrix reconstruction
Draft Accepted
Aboulnasr Hassanien / Wright State University, USA
Elias Aboutanios / University of New South Wales, Australia
In this paper, we consider the problem of adaptive beamforming for sample-starved scenarios. A beamforming design method is developed for the case when the only available data is a single-snapshot that is contaminated by the signal-of-interest.
Instead of using the non-invertible rank-one sample covariance matrix, the proposed method reconstructs the interference-plus-noise covariance matrix via estimating the interference signal components and the noise variance. The computationally efficient
fast iterative interpolated beamforming (FIIB) algorithm is used to estimate the spatial frequencies and complex amplitudes associated with the interference. The reconstructed covariance matrix is used for adaptive beamforming design. Unlike existing sparsity-based covariance reconstruction techniques, the proposed method is able to reconstruct off-grid interference components and its performance is shown to not suffer from estimation bias. Simulation examples are used to demonstrate the performance superiority of the proposed method over other adaptive single-snapshot beamforming techniques.
Important Date
  • Conference Date

    Jun 08

    2020

    to

    Jun 11

    2020

  • Jan 12 2020

    Draft paper submission deadline

  • Apr 15 2020

    Early Bird Registration

  • Dec 31 2020

    Registration deadline

Sponsored By
IEEE Signal Processing Society
Organized By
Zhejiang University
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