在未知相互合的传感器阵列中进行DOA估计的重量化离网稀疏频谱适配
Liangliang Li1, Xianpeng Wang1, Xiang Lan1
1State Key Laboratory of Marine Resource Utilization in South China Sea, School of Information and Communication Engineering, Hainan University, Haikou 570228, China.
Sensors (Basel, Switzerland)
|July 14, 2023
概括
这项研究引入了一种新的方法,用于在未知相互合的传感器阵列中估计到达方向 (DOA). 重量化离网散射频适配 (Re-OGSpSF) 方法可以高精度,高效地实现连续的DOA估计.
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:
- 在传感器阵列应用中,到达方向 (DOA) 估计至关重要.
- 传感器之间的未知相互合显著降低了传统的DOA估计性能.
- 使用稀疏回收的现有离网DOA估计方法是有限的,特别是在相互合下.
研究的目的:
- 在未知相互合的传感器阵列中调查离网DOA估计.
- 为具有挑战性的环境开发一种新且强大的DOA估计算法.
- 提高方向查找技术的准确性和效率.
主要方法:
- 建议采用重新加权的离网 Sparse Spectrum Fitting (Re-OGSpSF) 方法.
- 使用选择矩阵形成一个不受干扰的数组输出,以减轻相互合效应.
- 一个精细的离网SpSF模型集成了一个离网错误项,一个加权矩阵增强了稀疏性.
主要成果:
- Re-OGSpSF方法有效地消除了未知的相互合效应.
- 高精度的连续DOA估计是通过离网表示和重量化策略实现的.
- 与模拟中的现有技术相比,拟议的方法显示出更高的性能和效率.
结论:
- 开发的Re-OGSpSF方法为在未知的相互合下对离网DOA估计提供了可靠的解决方案.
- 该方法为实时定向应用提供了显著的优势.
- 模拟结果证实了拟议技术的有效性和优越性.
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