Raza, A. and Liu, W. orcid.org/0000-0003-2968-2888 (2016) Critical Analysis of the Eigenfilter Method for the Design of FIR Filters and Wideband Beamformers. In: 2016 22nd International Conference on Automation and Computing (ICAC). 2016 22nd International Conference on Automation and Computing (ICAC), 07-08 Sep 2016, Colchester, UK. IEEE ISBN 978-1-86218-132-8
Abstract
The least squares based eigenfilter method has been applied to the design of both finite impulse response (FIR) filters and wideband beamformers successfully. It involves calculating the resultant filter coefficients as the eigenvector of an appropriate Hermitian matrix, and offers lower complexity and less computation time with better numerical stability as compared to the standard least squares method. In this paper, we revisit the method and critically analyze the eigenfilter approach by revealing a serious performance issue in the passband of the designed FIR filter and the mainlobe of the wideband beamformer, which occurs due to a formulation problem. A solution is then proposed to mitigate this issue, and design examples for both FIR filters and wideband beamformers are provided to demonstrate the effectiveness of the proposed method.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 IEEE. This is an author produced version of a paper subsequently published in Automation and Computing (ICAC), 2016 22nd International Conference on. Uploaded in accordance with the publisher's self-archiving policy. |
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: | 08 Jul 2016 09:00 |
Last Modified: | 19 Dec 2022 13:34 |
Published Version: | https://doi.org/10.1109/IConAC.2016.7604970 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/IConAC.2016.7604970 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:101264 |