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Updated: Sep 11, 2025

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佩罗纳和马利克对到达方向的估计进行了调整,理查德森-卢西解卷
Tianfeng Huang1,2,3, Dajun Sun1,2,3, Yuriy Zakharov4
1National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China.
The Journal of the Acoustical Society of America
|August 15, 2025
概括
这项研究增强了理查德森-卢西 (RL) 算法,用于估计到达的水下声学方向. 将RL与Perona & Malik调节器相结合,可以在低信号对噪声条件下提高性能.
科学领域:
- 水下声学 水下声学
- 信号处理 信号处理
- 阵列信号处理系统的信号处理.
背景情况:
- 理查德森 - 卢西 (RL) 解卷算法对于在水下声波阵列中的到达方向 (DOA) 估计至关重要.
- 在较低的信号噪声比 (SNR) 时,RL算法的性能会降低,这是由于反向问题的不良性质.
研究的目的:
- 为了提高RL算法的性能,在具有挑战性的水下声学环境中进行DOA估计.
- 为了减轻RL算法在低SNR的性能下降.
主要方法:
- 提出了一种新的方法,将理查德森-卢西 (RL) 算法与佩罗纳和马利克调节器结合起来.
- 佩罗纳和马利克调节器被用来平滑梁侧叶和利目标峰,限制解决方案空间.
- 使用模拟和实验数据对传统光束成形,原始RL算法和总变异规范RL方法进行了性能评估.
主要成果:
- 与其他方法相比,使用佩罗纳和马利克调节剂的拟议RL表现出优越的性能.
- 实现了光束宽度的显著减少和多目标分辨率的改进.
- 成功降低侧叶水平,特别是在信号噪声比高于-10dB的情况下.
结论:
- 佩罗纳和马利克调节器的集成有效地增强了用于水下声学DOA估计的RL算法.
- 拟议的方法为改善分辨率和降低低SNR环境中的侧叶水平提供了强大的解决方案.
- 这一进步对于在复杂的水下声学场景中准确定位目标至关重要.
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