L型互质阵的虚拟共轭插值二维DOA估计方法

Two-Dimensional DOA Estimation Method of Virtual Conjugate Interpolation for L-Shaped Coprime Array

针对现有互质阵DOA估计方法无法充分利用非连续阵元信息和信号时域信息,而导致的DOA估计精度低、虚拟阵列的阵列孔径小和自由度少的问题,本文提出了一种L型互质阵的虚拟共轭插值二维DOA估计方法。该方法首先以L型互质阵的阵列接收数据为基础,通过求解其互相关函数,来构造虚拟共轭增广阵列的接收数据矩阵;然后通过阵列插值补零和选取协方差矩阵非零列,得到含有部分缺失项的虚拟均匀线阵接收数据矩阵,并依据原子范数的思想,构造无网格凸优化问题,对虚拟均匀线阵协方差矩阵的缺失项进行填充,再使用求根多重信号分类方法得到入射信号与x轴和z轴正方向夹角的估计值;最终基于虚拟信源功率的唯一性,通过构建相关代价函数实现各轴夹角估计值的匹配,进而根据各轴夹角与方位角和俯仰角的关系,得到相匹配的方位角和俯仰角估计值。本文方法提高了DOA估计精度,扩展了阵列孔径,提高了自由度,且通过求根多重信号分类方法,降低了计算复杂度。仿真实验结果表明,本文方法能够实现二维DOA估计与角度匹配,且相比于对比方法,本文方法能够估计更多的信号源,拥有更加优越的DOA估计性能。

This study proposes a two-dimensional direction-of-arrival(DOA)estimation method of virtual conjugate interpolation for an L-shaped coprime array to address the issue of existing DOA estimation methods,which cannot make full use of the discontinuous array element information and signal time domain information,leading to low DOA estimation accuracy,a small array aperture,and limited degrees of freedom.The method is first based on the received array data of the L-shaped coprime array.The received data matrix of the virtual conjugate augmented array is constructed by calculating its cross-correlation function.Then,by utilizing array interpolation zero-padding and selecting the non-zero columns of the covariance matrix,the received data matrix of the virtual uniform linear array with partially missing terms is obtained,and by the idea of atomic norms,the gridless convex optimization problem is constructed,the missing terms of the virtual uniform line array covariance matrix are filled,and the estimated values of the angles between the incoming signals and the x-and z-axis positive directions are obtained by using the root multiple signal classification method.Finally,based on the uniqueness of the virtual source power,the estimated angles of each axis are matched by constructing the relevant cost function,and then the azimuth and elevation angles are estimated and matched according to the relationship between the angle of each axis and the azimuth and elevation angles.This method improves the accuracy of DOA estimation,expands the array aperture,increases the degree of freedom,and reduces the computational complexity using the root multiple signal classification method.The simulation results show that the method proposed in this study can achieve two-dimensional DOA estimation and angle matching,and compared to the comparison method,the proposed method can estimate more signal sources and has better DOA estimation performance.