  In this paper, an algorithm of multiple signal classification (MUSIC) is
proposed for two-dimensional (2-D) direction of- arrival (DOA) and polarization
estimation of non-circular signal in three-dimensional (3-D) millimeter wave
polarized largescale/ massive multiple-input-multiple-output (MIMO) systems.
The traditional MUSIC-based algorithms can estimate either the DOA and
polarization for circular signal or the DOA for non-circular signal by using
spectrum search. By contrast, in the proposed algorithm only the DOA estimation
needs spectrum search, and the polarization estimation has a closedform
expression. First, a novel dimension-reduced MUSIC (DRMUSIC) is proposed for
DOA and polarization estimation of circular signal with low computational
complexity. Next, based on the quaternion theory, a novel algorithm named
quaternion non-circular MUSIC (QNC-MUSIC) is proposed for parameter estimation
of non-circular signal with high estimation accuracy. Then based on the DOA
estimation result using QNC-MUSIC, the polarization estimation of non-circular
signal is acquired by using the closed-form expression of the polarization
estimation in DR-MUSIC. In addition, the computational complexity analysis
shows that compared with the conventional DOA and polarization estimation
algorithms, our proposed QNC-MUSIC and DRMUSIC have much lower computational
complexity, especially when the source number is large. The stochastic
Cramer-Rao Bound (CRB) for the estimation of the 2-D DOA and polarization
parameters of the non-circular signals is derived as well. Finally, numerical
examples are provided to demonstrate that the proposed algorithms can improve
the parameter estimation performance when the large-scale/massive MIMO systems
are employed.

Signal Processing