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Fast Direction of Arrival Estimation for Uniform Circular Arrays With a Virtual Signal Subspace
IEEE Transactions on Aerospace and Electronic Systems ( IF 5.1 ) Pub Date : 2021-01-11 , DOI: 10.1109/taes.2021.3050667
Kaijie Xu , Yinghui Quan , Bowen Bie , Mengdao Xing , Weike Nie , Hanyu E

In this article, an augmented subspace-based algorithm for detecting the direction of arrival (DOA) of signals is presented. In the developed scheme, a uniform circular antenna array with a full range of lateral capacity is first transformed into a uniform linear antenna array in which the steering matrix has a Vandermonde form. This kind of structure can be exploited to formulate computationally efficient search-free estimation methods. In the process of virtual transformation, a novel DOA unit matrix of an assumed sector where the signals to be detected are located is built and optimized to find response matrices of the real and virtual antenna arrays to signals from the sector. By utilizing singular value decomposition (SVD) of the response matrix of the real antenna array to possible signals from the sector, a stable virtual transformation matrix between the real and virtual antenna arrays is obtained. Meanwhile, the aperture of the original array is also expanded during this process. Then, a virtual cyclic optimization algorithm is introduced to thoroughly mine information from the correlation matrices of the virtual antenna array receiving data and to optimize the signal subspace. Subsequently, the DOA can be efficiently determined through the reconstruction of the steering matrix. In the experimental part of the study, root-mean-square errors and probability of success are used to evaluate the performance of the algorithms. In particular, simulation results demonstrate that the proposed methods provide significant accuracy improvements, especially for low signal-to-noise ratio thresholds.

中文翻译:

具有虚拟信号子空间的均匀圆阵列的快速到达估计方向

在本文中,提出了一种用于检测信号到达方向 (DOA) 的基于增强子空间的算法。在开发的方案中,首先将具有全范围横向容量的均匀圆形天线阵列转化为均匀线性天线阵列,其中导向矩阵具有范德蒙形式。可以利用这种结构来制定计算效率高的无搜索估计方法。在虚拟变换过程中,建立并优化了待检测信号所在的假设扇区的新型DOA单元矩阵,以求出真实和虚拟天线阵列对该扇区信号的响应矩阵。通过利用真实天线阵列响应矩阵的奇异值分解 (SVD) 对来自扇区的可能信号,获得了真实和虚拟天线阵列之间的稳定虚拟变换矩阵。同时,原始阵列的孔径也在此过程中扩大。然后引入虚拟循环优化算法,从虚拟天线阵列接收数据的相关矩阵中彻底挖掘信息,优化信号子空间。随后,可以通过重建引导矩阵有效地确定 DOA。在研究的实验部分,均方根误差和成功概率用于评估算法的性能。特别是,仿真结果表明所提出的方法提供了显着的精度改进,特别是对于低信噪比阈值。同时,原始阵列的孔径也在此过程中扩大。然后引入虚拟循环优化算法,从虚拟天线阵列接收数据的相关矩阵中彻底挖掘信息,优化信号子空间。随后,可以通过重建引导矩阵有效地确定 DOA。在研究的实验部分,均方根误差和成功概率用于评估算法的性能。特别是,仿真结果表明所提出的方法提供了显着的精度改进,特别是对于低信噪比阈值。同时,原始阵列的孔径也在此过程中扩大。然后引入虚拟循环优化算法,从虚拟天线阵列接收数据的相关矩阵中彻底挖掘信息,优化信号子空间。随后,可以通过重建引导矩阵有效地确定 DOA。在研究的实验部分,均方根误差和成功概率用于评估算法的性能。特别是,仿真结果表明所提出的方法提供了显着的精度改进,特别是对于低信噪比阈值。引入虚拟循环优化算法,从虚拟天线阵列接收数据的相关矩阵中彻底挖掘信息,优化信号子空间。随后,可以通过重建引导矩阵有效地确定 DOA。在研究的实验部分,均方根误差和成功概率用于评估算法的性能。特别是,仿真结果表明所提出的方法提供了显着的精度改进,特别是对于低信噪比阈值。引入虚拟循环优化算法,从虚拟天线阵列接收数据的相关矩阵中彻底挖掘信息,优化信号子空间。随后,可以通过重建引导矩阵有效地确定 DOA。在研究的实验部分,均方根误差和成功概率用于评估算法的性能。特别是,仿真结果表明所提出的方法提供了显着的精度改进,特别是对于低信噪比阈值。在研究的实验部分,均方根误差和成功概率用于评估算法的性能。特别是,仿真结果表明所提出的方法提供了显着的精度改进,特别是对于低信噪比阈值。在研究的实验部分,均方根误差和成功概率用于评估算法的性能。特别是,仿真结果表明所提出的方法提供了显着的精度改进,特别是对于低信噪比阈值。
更新日期:2021-01-11
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