中文摘要：

针对相关信号的DOA估计和角度跟踪的传统算法自适应性差和特征值分解运算量大的问题,提出了一种基于实值特征子空间迭代的DOA估计算法.对每次快拍数据,通过梯度算法自适应更新信号和噪声子空间,并将复值特征子空间变换为实值,最后利用基于信号子空间的角度估计方法（Unitary ESPRIT）或噪声子空间的方法（实值域求根MUSIC）估计信号角度.由于引入了自适应特征子空间迭代和实值域处理,该算法无需特征值分解,有效地降低了基于子空间类高分辨算法的运算量,可以应用于相关信号的角度估计和跟踪问题.理论分析和仿真结果表明,算法具有较低的运算量和良好的自适应性,对某米波测高雷达实测数据的处理结果也表明了算法的有效性.

英文摘要：

A novel method for direction-of-arrival estimation of the correlated-signal is proposed to enhance the adaptability of the traditional high-resolution methods and to reduce the computational burden caused by eigen-decomposition and searching procedure.The noise subspace or signal subspace is iteratively obtained by the gradient algorithm for each snapshot,and then it is transformed from complex-valued space to real-valued space.Finally,Unitary ESPRIT or Root-MUSIC based on real-valued space is used to estimate the angles.Introduction of the eigen-subspace iteration and real-valued space processing eliminates eigen-decomposition,thus reducing the computational complexity significantly.The method can also be applied to the angle estimation and angle tracking problems for coherent signals.Simulations and real data processing results verify the effectiveness of the proposed method.