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Distributed Root-MUSIC Using Finite-Time Average Consensus

Chen, Po-Chih and Vaidyanathan, P. P. (2021) Distributed Root-MUSIC Using Finite-Time Average Consensus. In: 2021 55th Asilomar Conference on Signals, Systems, and Computers. IEEE , Piscataway, NJ, pp. 539-543. ISBN 978-1-6654-5828-3. https://resolver.caltech.edu/CaltechAUTHORS:20220317-376249000

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Abstract

Distributed (decentralized) algorithms for principal component analysis of covariance matrices are well-known, and their applications in array signal processing have received more interest recently. Inspired by this, a new distributed algorithm for the popular DOA estimation method, root-MUSIC, is proposed. The average consensus method is used to avoid the need for a fusion center in a sensor network, which makes the proposed algorithm fully distributed. In particular, the algorithm is based on a recently reported finite-time version of average consensus which converges to the exact solution in a finite number of iterations. This allows the proposed distributed root-MUSIC to achieve exactly the same performance as the centralized counterpart. The good performance of the proposed algorithm is verified by simulations.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/IEEECONF53345.2021.9723302DOIArticle
ORCID:
AuthorORCID
Chen, Po-Chih0000-0003-1637-9329
Vaidyanathan, P. P.0000-0003-3003-7042
Additional Information:© 2021 IEEE. This work was supported by the Office of Naval Research grant N00014-21-1-2521, and the California Institute of Technology.
Funders:
Funding AgencyGrant Number
Office of Naval Research (ONR)N00014-21-1-2521
CaltechUNSPECIFIED
Subject Keywords:Distributed, decentralized, finite-time average consensus, DOA estimation, root-MUSIC
DOI:10.1109/ieeeconf53345.2021.9723302
Record Number:CaltechAUTHORS:20220317-376249000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220317-376249000
Official Citation:P. -C. Chen and P. P. Vaidyanathan, "Distributed Root-MUSIC Using Finite-Time Average Consensus," 2021 55th Asilomar Conference on Signals, Systems, and Computers, 2021, pp. 539-543, doi: 10.1109/IEEECONF53345.2021.9723302
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113942
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:18 Mar 2022 19:56
Last Modified:18 Mar 2022 19:56

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