针对传统联合估计方法计算量大、需要多维谱峰搜索的问题，该文提出了一种基于垂直阵列结构的任意初始相位非圆信号2 维DOA (Direction Of Arrival)和初相联合估计方法，利用垂直阵列特点，将3维参数估计问题转化为可并行处理的3个2维参数估计，在每一个子阵上，同时使用噪声子空间正交性和信号子空间旋转不变性，将2维参数估计进一步转化为1维估计问题，最终只需要对扩展协方差矩阵进行一次特征分解即可实现2维DOA和初相的联合估计及自动配对。该方法适用于空间信源处于过载的情形和低信噪比、短快拍环境，可估计信源数为2(M−1)。数值仿真验证了该算法的有效性。
Classical joint estimation methods need large calculation quantity and multidimensional search. In order to avoid these shortcoming, a novel joint two-Dimension (2-D) Direction Of Arrival (DOA) and noncircularity phase estimation method based on three orthogonal linear arrays is proposed. The problem of 3-D parameter estimation can be transformed to three parallel 2-D parameter estimation according to the characteristic of three orthogonal linear arrays. Further more, the problem of 2-D parameter estimation can be transformed to 1-D parameter estimation by using the rotational invariance property among signal subspace and orthogonal property of noise subspace at the same time in every subarray. Ultimately, the algorithm can realize joint estimation and pairing parameters by one eigen-decomposition of extended covariance matrix. The proposed algorithm can be applicable for low SNR and small snapshot scenarios, and can estiame 2(M −1) signals. Simulation results verify that the proposed algorithm is effective.
