Shi Heping, Leng Wen, Guan Zhiwei, Jin Tongzhi
School of Automotion and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China.
School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.
Sensors (Basel). 2017 Jun 18;17(6):1433. doi: 10.3390/s17061433.
This paper addresses the two-dimensional (2D) direction-of-arrival (DOA) estimation problem with two novel methods for mixed noncircular and circular signals. The first proposed method is named the two-stage direction-of-arrival matrix (TSDOAM) method, and the other is called the two-stage rank reduction (TSRARE) method. The proposed methods utilize both the circularity and the direction-of-arrival differences between the noncircular and circular sources to estimate the 2D directions-of-arrival (DOAs). The maximum detectable 2D angle parameters of the TSDOAM and TSRARE methods are twice those of the existing methods. Moreover, the TSRARE method can detect more incident signals than the TSDOAM method due to the array aperture of two parallel uniform linear arrays (ULAs) being fully utilized. Simulation results show that compared to the existing methods for the small angle separation of 2D directions-of-arrival, the two proposed methods perform well in terms of the signal-to-noise ratio (SNR) and snapshots.
本文针对混合非循环信号和循环信号的二维（2D）到达方向（DOA）估计问题，提出了两种新方法。第一种方法称为两阶段到达方向矩阵（TSDOAM）方法，另一种方法称为两阶段秩缩减（TSRARE）方法。所提出的方法利用非循环源和循环源之间的循环性和到达方向差异来估计二维到达方向（DOA）。TSDOAM和TSRARE方法的最大可检测二维角度参数是现有方法的两倍。此外，由于充分利用了两个平行均匀线性阵列（ULA）的阵列孔径，TSRARE方法比TSDOAM方法能检测到更多的入射信号。仿真结果表明，与现有的二维到达方向小角度分离方法相比，所提出的两种方法在信噪比（SNR）和快照方面表现良好。
