Reducing errors for root‐MUSIC‐based methods in uniform circular arrays. Issue 1 (1st February 2018)

• Record Type: Journal Article
• Authors: Jiang, Guojun; Mao, Xingpeng; Liu, Yongtan
• Is Part Of: IET signal processing. Volume 12:Issue 1(2018)
• Page Start: 31
• Page End: 36
• Publication Date: 2018-02-01
• Subjects: signal classification -- direction‐of‐arrival estimation -- covariance matrices -- iterative methods; uniform circular arrays -- direction of arrival estimation -- beamspace transformation -- BT -- beamspace sample covariance matrix -- BSCM -- UCA root‐MUSIC‐based methods -- computational complexity -- estimation error; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/iet-spr.2016.0576
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract : Root‐MUSIC can be applied to uniform circular array (UCA) to achieve computationally efficient direction of arrival (DOA) estimation via beamspace transformation (BT). When the number of sensors of a UCA is small, the residual errors introduced by the BT will have significant values, resulting in performance degradation for DOA estimation. To solve this problem, an algorithm that enables the modification of the beamspace sample covariance matrix (BSCM) by considering the residual components is proposed. First, the residual components in the BSCM are calculated based on the initial DOAs estimated by the UCA root‐MUSIC‐based methods. Then the BSCM is modified by removing the undesirable terms. Finally, better DOA estimation performance is obtained by using the revised BSCM. The computational complexity and estimation error are derived. The significant advantages of the proposed algorithm are demonstrated by the simulation results.