Wang, J., Zhang, W. and Liu, W. orcid.org/0000-0003-2968-2888 (2018) Minimum Sensitivity Based Robust Beamforming with Eigenspace Decomposition. Multidimensional Systems and Signal Processing, 29 (2). pp. 687-701. ISSN 0923-6082,
Abstract
An enhanced eigenspace-based beamformer (ESB) derived using the minimum sensitivity criterion is proposed with significantly improved robustness against steering vector errors. The sensitivity function is defined as the squared norm of the appropriately scaled weight vector and since the sensitivity function of an array to perturbations becomes very large in the presence of steering vector errors, it can be used to find the best projection for the ESB, irrespective of the distribution of additive noises. As demonstrated by simulation results, the proposed method has a better performance than the classic ESBs and the previously proposed uncertainty set based approach.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Science+Business Media New York 2016. This is an author produced version of a paper subsequently published in Multidimensional Systems and Signal Processing. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Eigenspace; robust beamformer; minimum sensitivity |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 18 May 2016 09:30 |
Last Modified: | 06 Jun 2023 16:00 |
Status: | Published |
Publisher: | Springer Verlag |
Refereed: | Yes |
Identification Number: | 10.1007/s11045-016-0424-1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:99621 |