| Paper: | SAM-P3.2 | ||
| Session: | Beamforming and Space-Time Processing | ||
| Time: | Wednesday, May 17, 10:00 - 12:00 | ||
| Presentation: | Poster | ||
| Topic: | Sensor Array and Multichannel Signal Processing: Adaptive beamforming and direction of arrival estimation | ||
| Title: | Data Dimension Reduction Using Krylov Subspaces: Making Adaptive Beamformers Robust to Model Order-Determination | ||
| Authors: | Hongya Ge, New Jersey Institute of Technology, United States; Ivars Kirsteins, Naval Undersea Warfare Center, United States; Louis L. Scharf, Colorado State University, United States | ||
| Abstract: | In this work, we present a class of low-complexity reduced-dimension {\em adaptive} beamformers constructed from expanding Krylov subspaces. We demonstrate how the data dimensionality reduction obtained from Krylov pre-processing decreases the sensitivity of reduced-rank adaptive beamforming techniques to incorrect model-order selection and lessens the computational complexity of systems involving large arrays with many elements. An important advantage of the proposed dimensionality reduction scheme is that it relieves reduced-rank methods from the stringent requirement on the precise model order determination. | ||
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