Zhou Chengwei, Zhou Jinfang
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China.
Sensors (Basel). 2017 Aug 3;17(8):1779. doi: 10.3390/s17081779.
A coprime array is capable of achieving more degrees-of-freedom for direction-of-arrival (DOA) estimation than a uniform linear array when utilizing the same number of sensors. However, existing algorithms exploiting coprime array usually adopt predefined spatial sampling grids for optimization problem design or include spectrum peak search process for DOA estimation, resulting in the contradiction between estimation performance and computational complexity. To address this problem, we introduce the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) to the coprime coarray domain, and propose a novel coarray ESPRIT-based DOA estimation algorithm to efficiently retrieve the off-grid DOAs. Specifically, the coprime coarray statistics are derived according to the received signals from a coprime array to ensure the degrees-of-freedom (DOF) superiority, where a pair of shift invariant uniform linear subarrays is extracted. The rotational invariance of the signal subspaces corresponding to the underlying subarrays is then investigated based on the coprime coarray covariance matrix, and the incorporation of ESPRIT in the coarray domain makes it feasible to formulate the closed-form solution for DOA estimation. Theoretical analyses and simulation results verify the efficiency and the effectiveness of the proposed DOA estimation algorithm.
在使用相同数量传感器时,互质阵列在到达方向(DOA)估计方面比均匀线性阵列能够实现更多的自由度。然而,现有的利用互质阵列的算法通常采用预定义的空间采样网格进行优化问题设计,或者在DOA估计中包含频谱峰值搜索过程,这导致了估计性能与计算复杂度之间的矛盾。为了解决这个问题,我们将旋转不变技术估计信号参数(ESPRIT)引入互质协方差域,并提出一种基于互质协方差域ESPRIT的新型DOA估计算法,以有效地检索离网格DOA。具体而言,根据从互质阵列接收到的信号推导互质协方差统计量,以确保自由度(DOF)优势,从中提取一对平移不变均匀线性子阵列。然后基于互质协方差矩阵研究与基础子阵列对应的信号子空间的旋转不变性,并且在协方差域中引入ESPRIT使得为DOA估计制定闭式解成为可能。理论分析和仿真结果验证了所提出的DOA估计算法的有效性和高效性。