Distributed Root-MUSIC Using Finite-Time Average Consensus

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.

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