A Unified Array Geometry Composed of Multiple Identical Subarrays With Hole-Free Difference Coarrays for Underdetermined DOA Estimation

作者：Yang, Mingle^*; Haimovich, Alexander M.; Yuan, Xin; Suns, Lei; Chen, Baixiao

来源：IEEE Access, 2018, 6: 14238-14254.

DOI：10.1109/ACCESS.2018.2813313

• Coprime array
• difference coarray
• direction-of-arrival (DOA) estimation
• minimum redundancy array
• nested array
• sensor arrays

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((MN2)-N-2) 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.

• 出版日期2018
• 单位西安电子科技大学