2018IEEE Communications LettersRequires access

Extended-Aperture Unitary Root MUSIC-Based DOA Estimation for Coprime Array

Jianfeng Li, Dong Li, Defu Jiang, Xiaofei Zhang

Open publisher page 83 citations

Abstract

Direction of arrival (DOA) estimation using coprime array is studied, and an extended-aperture unitary root multiple signal classification (MUSIC)-based method is proposed. The geometry of prototype coprime array is modified through some translations, which enable one subarray of the coprime array to achieve aperture extension after unitary transformation. Then, the aperture of the other subarray can also be extended based on the rotational invariance of the extended subarray, and 2-D parameter estimations from the two extended subarrays can be achieved in succession via 1-D root MUSIC-based technique. Finally, unique DOA is determined from the intersection of the two automatically paired and coprime estimations. In contrast to the partial search MUSIC method, the estimation of signal parameters via rotational invariance technique based method, the root MUSIC-based method, and the real-valued cross covariance matrix based method, the proposed method gives better DOA estimation results and manages more sources. Furthermore, it has low complexity for the real-valued decomposition. Simulation results verify the improvement of the proposed approach.

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What this paper is about

Direction of arrival (DOA) estimation using coprime array is studied, and an extended-aperture unitary root multiple signal classification (MUSIC)-based method is proposed. The geometry of prototype coprime array is modified through some translations, which enable one subarray of the coprime array to achieve aperture extension after unitary transformation. Then, the aperture of the other subarray can also be extended based on the rotational invariance of the extended subarray, and 2-D parameter estimations from the two extended subarrays can be achieved in succession via 1-D root MUSIC-based technique. Finally, unique DOA is determined from the intersection of the two automatically paired and coprime estimations. In contrast to the partial search MUSIC method, the estimation of signal parameters via rotational invariance technique based method, the root MUSIC-based method, and the real-valued cross covariance matrix based method, the proposed method gives better DOA estimation results and manages more sources. Furthermore, it has low complexity for the real-valued decomposition. Simulation results verify the improvement of the proposed approach.

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Available abstract

Direction of arrival (DOA) estimation using coprime array is studied, and an extended-aperture unitary root multiple signal classification (MUSIC)-based method is proposed. The geometry of prototype coprime array is modified through some translations, which enable one subarray of the coprime array to achieve aperture extension after unitary transformation. Then, the aperture of the other subarray can also be extended based on the rotational invariance of the extended subarray, and 2-D parameter estimations from the two extended subarrays can be achieved in succession via 1-D root MUSIC-based technique. Finally, unique DOA is determined from the intersection of the two automatically paired and coprime estimations. In contrast to the partial search MUSIC method, the estimation of signal parameters via rotational invariance technique based method, the root MUSIC-based method, and the real-valued cross covariance matrix based method, the proposed method gives better DOA estimation results and manages more sources. Furthermore, it has low complexity for the real-valued decomposition. Simulation results verify the improvement of the proposed approach.

Key concepts: Coprime integers, Rotational invariance, Direction of arrival, Algorithm, Computer science, Unitary state, Mathematics, Unitary transformation

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