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Two-Dimensional Direction-of-Arrival Estimation Based on Augmented Lagrange Multiplier for Multiband Integrated Sparse Array

机译:基于增强拉格朗日乘法器的多频集成稀疏阵列的二维方向估计

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To achieve underdetermined 2-D DOA estimation of signals in different band, a novel integrated sparse array based on four rectangular sparse subarrays with reduced coupling effect and a 2-D DOA estimator via matrix completion are proposed. Firstly, the concept of original rectangular uniform array (ORUA) is proposed and the nested Toeplitz characteristic of covariance matrix is analysed. Then nested Toeplitz covariance matrix is estimated quickly by augmented Lagrange multiplier. Based on the precisely estimated covariance matrix, we achieve 2-D DOA estimation with unitary-ESPRIT. Simulation results demonstrate that our proposed algorithm can achieve superior 2-D DOA estimation performance and high estimation accuracy.
机译:为了实现不同频带中的信号的未定定的2-D DOA估计,提出了一种基于具有降低的耦合效应的四个矩形稀疏子阵列的新型集成稀疏阵列和经由矩阵完成的2-D DOA估计器。 首先,提出了原始矩形均匀阵列(ORUA)的概念,分析了协方差矩阵的嵌套Toeplitz特征。 然后通过增强拉格朗日乘数估计嵌套Toeplitz协方差矩阵。 基于精确估计的协方差矩阵,我们通过单一esprit实现了2-D DOA估计。 仿真结果表明,我们所提出的算法可以实现优越的2-D DOA估计性能和高估计精度。

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