Name
Abstract | ||
|---|---|---|
We present low-complexity, quickly converging robust adaptive beamformers, for beamforming large arrays in snapshot deficient scenarios. The proposed algorithms are derived by combining data-dependent Krylov-subspace-based dimensionality reduction, using the Powers-of-R or conjugate gradient (CG) techniques, with ellipsoidal uncertainty set based robust Capon beamformer methods. Further, we provide a detailed computational complexity analysis and consider the efficient implementation of automatic, online dimension-selection rules. We illustrate the benefits of the proposed approaches using simulated data. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TAES.2014.130485 | Aerospace and Electronic Systems, IEEE Transactions |
Keywords | Field | DocType |
Robustness,Transforms,DH-HEMTs,Vectors,Ellipsoids,Array signal processing,Symmetric matrices | Conjugate gradient method,Krylov subspace,Beamforming,Adaptive beamformer,Dimensionality reduction,Robustness (computer science),Electronic engineering,Capon,Mathematics,Computational complexity theory | Journal |
Volume | Issue | ISSN |
51 | 1 | 0018-9251 |
Citations | PageRank | References |
20 | 0.57 | 44 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samuel Dilshan Somasundaram | 1 | 47 | 4.66 |
| Nigel H. Parsons | 2 | 29 | 1.84 |
| Peng Li | 3 | 20 | 0.57 |
| de Lamare, R.C. | 4 | 652 | 33.42 |