基于宽带均匀同心球阵列的低复杂度二维波达方向估计算法

该文提出一种基于宽带均匀同心球阵列(UCSA)的2维波达方向(2D-DOA)低复杂度估计算法。该方法将宽带UCSA输出信号转换为相位模式，并对其进行频率补偿，实现近似频率不变(FI)特性，从而降低宽带信号处理的计算复杂度。为了进一步降低2D-DOA估计的计算复杂度，该文提出基于FI-UCSA的降维多重信号分类(MUSIC)算法。该方法将相位模式导向向量分解为方位角和仰角相关的两个矩阵，从而把2维搜索问题简化为1维(1D)搜索，实现降维优化并降低计算复杂度。仿真结果表明，该算法计算复杂度相较于2维MUSIC算法得到了极大的降低，并且在估计精度和分辨率上均稍有改善。

Low Complexity Two-Dimensional Direction Of Arrival Estimation Using Wideband Uniform Concentric Spherical Arrays

A low complexity Two-Dimensional Direction Of Arrival (2D-DOA) estimation algorithm using wideband Uniform Concentric Spherical Arrays (UCSA) is proposed in this paper. The output signals of the wideband UCSA are firstly converted to phase mode signals, which are then compensated by filters to achieve Frequency Invariant (FI) characteristic. The FI characteristic of the array can reduce the computational complexity of the wideband signal processing. To reduce further the complexity of 2D-DOA estimation, a reduced-dimension MUltiple SIgnal Classification (MUSIC) algorithm using FI-UCSA is proposed. The equivalent steering vector of the phase mode signal is decomposed into two matrices, which are related to azimuth and elevation angles, respectively. The 2D MUSIC is then simplified to One-Dimensional (1D) search, which optimizes DOA estimation in reduced dimension and substantially lower the computation complexity. Simulation results show that the computational complexity of the proposed algorithm is greatly reduced compared with the 2D MUSIC algorithm. In addition, the estimation accuracy and the resolution are slightly improved.