MIMO声呐的双尺度旋转不变子空间波达方向估计*

为了提高单基地多输入多输出(Multiple-Input Multiple-Output, MIMO)声呐阵列的波达方向(Direction of arrival, DOA)估计性能,提出了双尺度旋转不变子空间(Dual-Resolution Estimation of Signal Parameters via Rotational Invariance Techniques, DR-ESPRIT)算法。结合MIMO阵列虚拟阵列的结构特征,首先利用ESPRIT算法通过各条虚拟线阵内、基线间距不大于半波长的子阵间的旋转不变关系得到无模糊的粗估计结果,之后利用虚拟线阵间、基线较长的子阵间的旋转不变关系得到一组有模糊的精估计结果。参考粗估计结果对精估计结果进行解模糊,最终得到高精度无模糊的角度估计结果。为了降低运算复杂度,利用该思路对降维ESPRIT算法也进行改进,提出了双尺度降维ESPRIT算法。仿真试验首先验证了与传统算法相比,双尺度类DOA估计算法能够有效提高角度估计精度。此外,还分析了MIMO声呐阵列的发射、接收阵元的幅相扰动误差对算法角度估计性能的影响。

DOA estimation in MIMO sonar based on dual-resolution ESPRIT algorithm

In order to improve the performance of direction of arrival (DOA) algorithm in multiple-input multiple-output(MIMO) sonar, a dual-resolution estimation of signal parameters via rotational invariance techniques(DR-ESPRIT) algorithm is proposed. Based on the construction of virtual array of MIMO sonar array, a low-accuracy but unambiguous coarse estimation is obtained by ESPRIT algorithm though the rotational invariance of short-baseline subarrays. Then, a series of high-accuracy but ambiguous fine estimation can be obtained though the rotational invariance of long-baseline subarrays. Referring to the unambiguous coarse estimation, high-accuracy and ambiguous estimation can be obtained through disambiguation method. In order to reduce the computational burden, dual-resolution estimation is also applied to reduced-dimensional ESPRIT algorithm and dual-resolution reduced-dimensional ESPRIT algorithm is proposed. Compared with conventional ESPRIT algorithm, dual-resolution DOA estimation algorithm can improve the estimation accuracy effectively. The influence of the amplitude and phase disturbance errors of transmitting and receiving arrays on the estimation performance of different algorithms is analyzed through simulation.