分布式nested阵列及其高精度DOA估计

为了进一步提高分布式阵列的自由度和分辨力,提出一种分布式nested阵列。该阵列将nested阵列作为分布式阵列的子阵。基于Khatri Rao积, nested子阵可提高整个阵列的自由度。分布式nested阵列以较少的阵元数及硬件成本实现大的孔径和较高的分辨力,而且提高了目标波达方向(direction of arrival, DOA)估计的精度。并利用基于Khatri Rao积的空间平滑酉旋转不变子空间(estimation of signal parameters via rotational invariance techniques, ESPRIT)算法进行DOA估计。其先对协方差矩阵向量化提高自由度,然后利用空间平滑对新数据协方差矩阵进行秩恢复,最后使用双尺度酉ESPRIT算法得到DOA估计。仿真结果证明所提方法的有效性。

High accuracy DOA estimation using separated nested array

To further improve the degrees of freedom and resolution of separated coherent arrays, a novel separated nested array is proposed. The nested arrays are used as the subarrays of the separated array. Based on the Khatri-Rao product, the nested subarrays can improve the degrees of freedom of the separated nested array. The separated nested array possesses large aperture and high resolution with low hardware cost and improves direction of arrival(DOA)estimation accuracy. The spatial smoothing unitary estimation of signal parameters via rotational invariance techniques(ESPRIT)based on the Khatri-Rao product is proposed to implement the DOA estimation. The covariance matrix is vectorized to improve the degrees of freedom and the spatial smoothing is used to build up the rank of the new covariance matrix, and then the DOA estimation is obtained using the dual size unitary ESPRIT algorithm. Simulation results are given to verify the effectiveness of the proposed method.