A Unified Array Geometry Composed of Multiple Identical Subarrays with Hole-Free Difference Coarrays for Underdetermined DOA Estimation
Document Type
Article
Publication Date
3-7-2018
Abstract
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.
Identifier
85043358777 (Scopus)
Publication Title
IEEE Access
External Full Text Location
https://doi.org/10.1109/ACCESS.2018.2813313
e-ISSN
21693536
First Page
14238
Last Page
14254
Volume
6
Grant
B18039
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Yang, Minglei; Haimovich, Alexander M.; Yuan, Xin; Sun, Lei; and Chen, Baixiao, "A Unified Array Geometry Composed of Multiple Identical Subarrays with Hole-Free Difference Coarrays for Underdetermined DOA Estimation" (2018). Faculty Publications. 8791.
https://digitalcommons.njit.edu/fac_pubs/8791
