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Sliding-Capon Based Convolutional Beamspace for Linear Arrays

Chen, Po-Chih and Vaidyanathan, P. P. (2021) Sliding-Capon Based Convolutional Beamspace for Linear Arrays. In: 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE , Piscataway, NJ, pp. 4565-4569. ISBN 9781728176055.

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A new method to design the filter for convolutional beamspace (CBS), called Capon-CBS, is proposed. The idea is to design the filter to be a sliding Capon beamformer. Such design takes input statistics into account, so it can do a better job of suppressing the sources that fall in the stopband. Capon-CBS can offer higher probability of resolution and smaller mean square error for DOA estimation, as demonstrated in the simulations. Moreover, like traditional CBS, Capon-CBS also has the advantage of low computational complexity.

Item Type:Book Section
Related URLs:
URLURL TypeDescription
Chen, Po-Chih0000-0003-1637-9329
Vaidyanathan, P. P.0000-0003-3003-7042
Additional Information:© 2021 IEEE. This work was supported in parts by the ONR grant N00014-18-1-2390, the NSF grant CCF-1712633, and the California Institute of Technology.
Funding AgencyGrant Number
Office of Naval Research (ONR)N00014-18-1-2390
Subject Keywords:Convolutional beamspace, Capon, beamforming, DOA estimation, MUSIC
Record Number:CaltechAUTHORS:20210601-150636010
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Official Citation:P. -C. Chen and P. P. Vaidyanathan, "Sliding-Capon Based Convolutional Beamspace for Linear Arrays," ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 4565-4569, doi: 10.1109/ICASSP39728.2021.9414022
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109330
Deposited By: Tony Diaz
Deposited On:01 Jun 2021 22:13
Last Modified:01 Jun 2021 22:13

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