基于修正ESPRIT算法的二维DOA估计

2-D DOA estimation based on a modified ESPRIT algorithm

针对二维ESPRIT算法在求解相干信号的时候存在较大的阵列冗余度,为了降低计算量,提高算法的解相干能力,在双排平行均匀线阵的基础上,介绍了一种二维修正ESPRIT算法.通过对子阵的合并,摒弃了原协方差矩阵中的冗余数据,使得新构成的协方差矩阵的维数比原来下降了近33%,从而降低了特征值分解的维数,并且新构成的协方差矩阵可以对接收数据进行共轭重排再利用.理论分析和仿真实验表明,该算法降低了计算量,提高了对非相干信号的估计准确度,同时具有一定的解相干能力.

When we use the ESPRIT algorithm to treat two-dimensional coherent signals there is a lot of redundancy in the arrays. In order to reduce computational effort and improve ability to deal with problems involving coherent sources, a new 2-D modified ESPRIT algorithm is proposed based on two parallel uniform linear arrays. With this algorithm, redundant data in the correlation matrix can be eliminated by merging the sub-arrays so that the size of the newly formed correlation matrix is decreased by 33%. This similarly reduces the dimensions of the eigenvalue decomposition, moreover, the conjugate data can be reused in the new correlation matrix. Compared with the conventional 2-D ESPRIT algorithm, the modifications presented reduce computing effort, improve precision and enhance its performance with coherent sources. The validity of the algorithm and accuracy of the theoretical analysis were verified by computer simulations.