TY - JOUR
T1 - A Unified Array Geometry Composed of Multiple Identical Subarrays with Hole-Free Difference Coarrays for Underdetermined DOA Estimation
AU - Yang, Minglei
AU - Haimovich, Alexander M.
AU - Yuan, Xin
AU - Sun, Lei
AU - Chen, Baixiao
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61571344, in part by the Fund for Foreign Scholars in University Research and Teaching Programs (the 111 Project) under Grant B18039, and in part by the China Scholarship Council.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/3/7
Y1 - 2018/3/7
N2 - In this paper, we propose a unified array geometry, dubbed generalized nested subarray (GNSA), for the underdetermined direction-of-arrival estimation. The GNSA is composed of multiple, identical subarrays, which can be a minimum redundancy array (MRA), a (super) nested array, a uniform linear array (ULA), or any other linear arrays with hole-free difference coarrays (DCAs). By properly design the spacings between subarrays, the resulting DCA of the GNSA can also be a hole-free (filled) ULA. When the subarray is an MRA and meanwhile its sensors' positions also follow an MRA configuration, a nested MRA (NMRA) is constructed. This NMRA can provide up to O(M2N2) degrees of freedom (DOFs) using only MN physical sensors. In order to fully utilize the increased DOF, we develop a new DOA estimation algorithm, which consists of a dimensional reduction matrix to exploit the data of all virtual elements, a Toeplitz matrix to decorrelate the equivalent coherent sources, and a root-MUSIC method to mitigate the computational workload. This new algorithm can achieve better DOA estimation performance than traditional spatial smoothing MUSIC algorithm with lower computational complexity. Numerical simulation results demonstrate the superiorities of the proposed array geometry in resolving more sources than sensors, DOA estimation performance, and the angular resolution.
AB - In this paper, we propose a unified array geometry, dubbed generalized nested subarray (GNSA), for the underdetermined direction-of-arrival estimation. The GNSA is composed of multiple, identical subarrays, which can be a minimum redundancy array (MRA), a (super) nested array, a uniform linear array (ULA), or any other linear arrays with hole-free difference coarrays (DCAs). By properly design the spacings between subarrays, the resulting DCA of the GNSA can also be a hole-free (filled) ULA. When the subarray is an MRA and meanwhile its sensors' positions also follow an MRA configuration, a nested MRA (NMRA) is constructed. This NMRA can provide up to O(M2N2) degrees of freedom (DOFs) using only MN physical sensors. In order to fully utilize the increased DOF, we develop a new DOA estimation algorithm, which consists of a dimensional reduction matrix to exploit the data of all virtual elements, a Toeplitz matrix to decorrelate the equivalent coherent sources, and a root-MUSIC method to mitigate the computational workload. This new algorithm can achieve better DOA estimation performance than traditional spatial smoothing MUSIC algorithm with lower computational complexity. Numerical simulation results demonstrate the superiorities of the proposed array geometry in resolving more sources than sensors, DOA estimation performance, and the angular resolution.
KW - Coprime array
KW - difference coarray
KW - direction-of-arrival (DOA) estimation
KW - minimum redundancy array
KW - nested array
KW - sensor arrays
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U2 - 10.1109/ACCESS.2018.2813313
DO - 10.1109/ACCESS.2018.2813313
M3 - Article
AN - SCOPUS:85043358777
SN - 2169-3536
VL - 6
SP - 14238
EP - 14254
JO - IEEE Access
JF - IEEE Access
ER -