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对于coprime平面数组的二维DOA估计:从数组结构设计到维度减小根MUSIC算法
Yunhe Shi1, Xiaofei Zhang1, Shengxinlai Han1
1College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Sensors (Basel, Switzerland)
|March 17, 2025
概括
这项研究引入了一种新的互补对比平面数组 (CCPA) 和一个有效的算法,用于二维到达方向 (2D-DOA) 估计. CCPA设计和根MUSIC算法提高了准确性,并减少了2D-DOA系统的计算负载.
科学领域:
- 信号处理 信号处理
- 阵列信号处理 阵列信号处理
- 电磁学 电磁学 电磁学 电磁学
背景情况:
- 准确的二维到达方向 (2D-DOA) 估计对于各种应用至关重要.
- 传统的方法往往需要复杂的数组或遭受高计算成本.
- 稀疏阵列提供了一个潜在的解决方案,但需要仔细设计以最大限度地提高性能.
研究的目的:
- 为提议一种新的稀疏阵列设计,即补充对等平面阵列 (CCPA),用于增强的2D-DOA估计.
- 为CCPA开发一个高效的缩小维数的根MUSIC算法.
- 改进自由度 (DOF) 和空间覆盖,同时降低计算复杂性.
主要方法:
- 通过分析coprime数组孔分布和添加补充元素来设计CCPA.
- 阵列的虚拟化以增加DOF和虚拟光圈.
- 通过将2D光谱搜索分解为1D根查找问题,开发了一个缩小维度的根MUSIC算法.
主要成果:
- CCPA设计增强了连续的DOF和虚拟光圈,使用更少的物理元素.
- 拟议的算法大大降低了2D-DOA估计的计算复杂性.
- 与现有方法相比,模拟显示出优越的估计性能,更高的DOF和更低的复杂性.
结论:
- CCPA提供了一种有效的稀疏阵列设计,用于改进2D-DOA估计.
- 维度减小根MUSIC算法提供了一个计算效率高和准确的解决方案.
- 合并的框架为2D-DOA应用程序推进了稀疏阵列设计和信号处理.
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