College of Automation, Harbin Engineering University, Harbin 150001, China.
Sensors (Basel). 2019 Feb 9;19(3):707. doi: 10.3390/s19030707.
Coprime arrays have shown potential advantages for direction-of-arrival (DOA) estimation by increasing the number of degrees-of-freedom in the difference coarray domain with fewer physical sensors. In this paper, a new DOA estimation algorithm for coprime array based on the estimation of signal parameter via rotational invariance techniques (ESPRIT) is proposed. We firstly derive the observation vector of the virtual uniform linear array but the covariance matrix of this observation vector is rank-deficient. Different from the traditional Toeplitz matrix reconstruction method using the observation vector, we propose a modified Toeplitz matrix reconstruction method using any non-zero row of the covariance matrix in the virtual uniform linear array. It can be proved in theory that the reconstructed Toeplitz covariance matrix has full rank. Therefore, the improved ESPRIT method can be used for DOA estimation without peak searching. Finally, the closed-form solution for DOA estimation in coprime array is obtained. Compared to the traditional coprime multiple signal classification (MUSIC) methods, the proposed method circumvents the use of spatial smoothing technique, which usually results in performance degradation and heavy computational burden. The effectiveness of the proposed method is demonstrated by numerical examples.
互质阵列通过使用更少的物理传感器在差分协阵列域中增加自由度,已经显示出在到达方向(DOA)估计方面的潜在优势。在本文中,提出了一种基于旋转不变技术估计信号参数(ESPRIT)的互质阵列 DOA 估计新算法。我们首先导出虚拟均匀线性阵列的观测向量,但该观测向量的协方差矩阵是秩亏的。与传统使用观测向量的 Toeplitz 矩阵重构方法不同,我们提出了一种使用虚拟均匀线性阵列中的协方差矩阵的任何非零行的改进的 Toeplitz 矩阵重构方法。可以从理论上证明重构的 Toeplitz 协方差矩阵具有满秩。因此,改进的 ESPRIT 方法可以用于 DOA 估计,而无需进行峰值搜索。最后,得到了互质阵列中 DOA 估计的闭式解。与传统的互质多重信号分类(MUSIC)方法相比,所提出的方法避免了使用空间平滑技术,这通常会导致性能下降和计算负担加重。数值示例验证了所提出方法的有效性。