Distributed Root-MUSIC Using Finite-Time Average Consensus

Po Chih Chen, P. P. Vaidyanathan

研究成果: Conference contribution同行評審

摘要

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.

原文English
主出版物標題55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
編輯Michael B. Matthews
發行者IEEE Computer Society
頁面539-543
頁數5
ISBN(電子)9781665458283
DOIs
出版狀態Published - 2021
事件55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 - Virtual, Pacific Grove, 美國
持續時間: 31 10月 20213 11月 2021

出版系列

名字Conference Record - Asilomar Conference on Signals, Systems and Computers
2021-October
ISSN(列印)1058-6393

Conference

Conference55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
國家/地區美國
城市Virtual, Pacific Grove
期間31/10/213/11/21

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