Direction-of-Arrival Estimation for Coprime Array via Virtual Array Interpolation

Chengwei Zhou, Yujie Gu, Xing Fan, Zhiguo Shi, Guoqiang Mao, Yimin D. Zhang

Research output: Contribution to journalArticlepeer-review

565 Scopus citations

Abstract

Coprime arrays can achieve an increased number of degrees of freedom by deriving the equivalent signals of a virtual array. However, most existing methods fail to utilize all information received by the coprime array due to the non-uniformity of the derived virtual array, resulting in an inevitable estimation performance loss. To address this issue, we propose a novel virtual array interpolation-based algorithm for coprime array direction-of-arrival (DOA) estimation in this paper. The idea of array interpolation is employed to construct a virtual uniform linear array such that all virtual sensors in the non-uniform virtual array can be utilized, based on which the atomic norm of the second-order virtual array signals is defined. By investigating the properties of virtual domain atomic norm, it is proved that the covariance matrix of the interpolated virtual array is related to the virtual measurements under the Hermitian positive semi-definite Toeplitz condition. Accordingly, an atomic norm minimization problem with respect to the equivalent virtual measurement vector is formulated to reconstruct the interpolated virtual array covariance matrix in a gridless manner, where the reconstructed covariance matrix enables off-grid DOA estimation. Simulation results demonstrate the performance advantages of the proposed DOA estimation algorithm for coprime arrays.

Original languageEnglish
Article number8472789
Pages (from-to)5956-5971
Number of pages16
JournalIEEE Transactions on Signal Processing
Volume66
Issue number22
DOIs
StatePublished - 15 Nov 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Funding

Manuscript received April 23, 2017; revised October 15, 2017, February 7, 2018, June 19, 2018, and July 31, 2018; accepted September 14, 2018. Date of publication September 26, 2018; date of current version October 10, 2018. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Romain Couillet. The work of C. Zhou, X. Fan, and Z. Shi was supported in part by the National Natural Science Foundation of China under Grant 61772467, in part by Zhejiang Provincial Natural Science Foundation of China under Grant LR16F010002, in part by the 973 Project under Grant 2015CB352503, and in part by the Fundamental Research Funds for the Central Universities under Grant 2017XZZX009-01. This paper was presented in part at the IEEE 85th Vehicular Technology Conference, Sydney, NSW, Australia, Jun. 2017 [1]. (Corresponding authors: Zhiguo Shi and Yujie Gu.) C. Zhou is with the College of Information Science and Electronic Engineering and the State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China (e-mail:,[email protected]).

FundersFunder number
973 Project2015CB352503
Zhejiang Provincial Natural Science Foundation of ChinaLR16F010002
National Natural Science Foundation of China61772467
Fundamental Research Funds for the Central Universities2017XZZX009-01

    Keywords

    • Atomic norm
    • coprime array
    • direction-of-arrival estimation
    • gridless Toeplitz matrix reconstruction
    • virtual array interpolation

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