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Information 2018, 9(11), 277; https://doi.org/10.3390/info9110277

Direction of Arrival Estimation Using Augmentation of Coprime Arrays

School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
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Received: 17 September 2018 / Revised: 1 November 2018 / Accepted: 6 November 2018 / Published: 9 November 2018
(This article belongs to the Section Information and Communications Technology)
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Abstract

Recently, direction of arrival (DOA) estimation premised on the sparse arrays interpolation approaches, such as co-prime arrays (CPA) and nested array, have attained extensive attention because of the effectiveness and capability of providing higher degrees of freedom (DOFs). The co-prime array interpolation approach can detect O(MN) paths with O(M + N) sensors in the array. However, the presence of missing elements (holes) in the difference coarray has limited the number of DOFs. To implement co-prime coarray on subspace based DOA estimation algorithm namely multiple signal classification (MUSIC), a reshaping operation followed by the spatial smoothing technique have been presented in the literature. In this paper, an active coarray interpolation (ACI) is proposed to efficiently recovering the covariance matrix of the augmented coarray from the original covariance matrix of source signals with no vectorizing and spatial smoothing operation; thus, the computational complexity reduces significantly. Moreover, the numerical simulations of the proposed ACI approach offers better performance compared to its counterparts. View Full-Text
Keywords: coarray interpolation; degree of freedom; nuclear norm minimization; DOA estimation; co-prime array; MUSIC; uniform linear array; sparse array coarray interpolation; degree of freedom; nuclear norm minimization; DOA estimation; co-prime array; MUSIC; uniform linear array; sparse array
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Hassan, T.U.; Gao, F.; Jalal, B.; Arif, S. Direction of Arrival Estimation Using Augmentation of Coprime Arrays. Information 2018, 9, 277.

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