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一种用于嵌套平面阵列的计算高效且无虚拟化的二维波达方向估计方法:RD-根-多重信号分类算法

A Computationally Efficient and Virtualization-Free Two-Dimensional DOA Estimation Method for Nested Planar Array: RD-Root-MUSIC Algorithm.

作者信息

Han Shengxinlai, Lai Xin, Zhang Yu, Zhang Xiaofei

机构信息

College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

出版信息

Sensors (Basel). 2022 Jul 13;22(14):5220. doi: 10.3390/s22145220.

Abstract

To address the problem of expensive computation in traditional two-dimensional (2D) direction of arrival (DOA) estimation, in this paper, we propose a 2D DOA estimation method based on a reduced dimension and root-finding MUSIC algorithm for nested planar arrays (NPAs). Specifically, the algorithm proposed in this paper transforms the problem based on 2D spectral peak search into two one-dimensional estimation problems by reducing the dimension, and then transforms the one-dimensional estimation problem into a problem of polynomial root finding. Finally the parameters are paired to realize the 2D DOA estimation. The proposed algorithm not only performs two root finding operations directly according to the 2D spectral function transformation, avoiding the performance degradation caused by intermediate operations, but can also fully exploit the enlarged array aperture offered by NPAs with reduced computational complexity and no need for virtualization. The superiorities of the proposed algorithm in terms of estimation accuracy and complexity are verified by simulations.

摘要

为了解决传统二维波达方向(DOA)估计中计算成本高昂的问题,本文提出了一种基于降维和求根MUSIC算法的嵌套平面阵列(NPA)二维DOA估计方法。具体而言,本文提出的算法通过降维将基于二维谱峰搜索的问题转化为两个一维估计问题,然后将一维估计问题转化为多项式求根问题。最后对参数进行配对以实现二维DOA估计。所提算法不仅根据二维谱函数变换直接执行两次求根操作,避免了中间操作导致的性能下降,而且还能充分利用NPA提供的扩大阵列孔径,同时降低计算复杂度且无需虚拟。通过仿真验证了所提算法在估计精度和复杂度方面的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eeb4/9325100/f297bb976c5f/sensors-22-05220-g001.jpg

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