一致的DOA估计算法与低SNR信号的共质数组
Fan Zhang1, Hui Cao1, Kehao Wang1
1School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China.
Sensors (Basel, Switzerland)
|December 9, 2023
概括
本研究介绍了用于估计到达方向 (DOA) 的增强空间平滑 (ESS) 算法. 在低信号噪声比 (SNR) 条件下,ESS算法提高了性能,实现了高精度和分辨率.
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) 估计对于雷达和无线通信等应用至关重要.
- 传统的方法难以提供连贯的信号,低信号噪声比 (SNR) 和有限的快照.
- 同级数组提供优势,但需要强大的估计技术.
研究的目的:
- 开发一种改进的算法,用于在co-prime数组中对一致信号的到达方向 (DOA) 估计.
- 在具有挑战性的条件下克服现有的空间平滑和子空间算法的局限性.
- 在准确性,分辨率和稳定性方面提高DOA估计的性能.
主要方法:
- 一个增强的空间平滑 (ESS) 算法被开发出来,结合了时空相关性矩阵.
- 该ESS算法使用了消除噪音和脱凝的技术.
- 通过旋转不变技术 (ESPRIT) 算法估计信号参数用于最终的DOA估计.
主要成果:
- 拟议的ESS算法与其他脱凝方法相比,显示出更高的性能.
- 在 -8 dB的SNR和150个快照时,平均平方误差 (MSE) 接近克拉梅尔-拉奥边界 (CRB).
- 在角分辨率大于4°的情况下,分辨率概率 (PoR) 超过88%,估计准确度超过90%.
结论:
- 增强空间平滑 (ESS) 算法有效地通过连贯的信号解决了DOA估计挑战.
- 该算法在低SNR和有限的快照场景中提供了显著的改进.
- ESS为在co-prime数组中DOA估计提供了强大而准确的解决方案.
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