一个增强的空间平滑技术的连贯的DOA估计与移动的coprime数组
Meng Yang1, Yu Zhang1, Yuxin Sun1
1College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
这项研究引入了一种增强的空间平滑方法,用于使用具有连贯信号的移动代数组 (MCA) 来估计到达方向 (DOA). 这种新的方法提高了DOA估计的准确性,特别是在信号噪声比较低的环境中.
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:
- 到达方向 (DOA) 估计对于各种应用至关重要.
- 一致的信号和稀疏的数组对传统的DOA估计方法构成挑战.
- 现有的空间平滑技术与稀疏数组不兼容,例如移动共类数组 (MCA).
研究的目的:
- 开发一种增强的空间平滑方法,用于使用MCA对连贯信号的DOA估计.
- 克服传统方法在稀疏数组配置中的局限性.
- 为了使像MUSIC这样的超分辨率算法能够在具有挑战性的场景中应用.
主要方法:
- 将不同时间的MCA信号结合起来,创建一个虚拟密集阵列.
- 计算共变矩阵并通过自身值分解推导信号子空间.
- 在信号子空间中应用增强的空间平滑来恢复等级.
主要成果:
- 拟议的方法使用MUSIC算法成功估计了连贯信号的DOA.
- 与传统技术相比,模拟结果显示出更高的性能.
- 在低信号噪声比条件下观察到显著的改善.
结论:
- 增强的空间平滑方法有效地解决了DOA估计的挑战,在MCA中提供了连贯的信号.
- 这种技术扩大了超分辨率算法在稀疏数组系统中的适用性.
- 拟议的算法提供了一个强大的解决方案,以提高DOA估计的准确性.
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