使用端到端网络的反响抑制波器的构建方法
Zhen Wang1, Hao Zhang1,2, Xiao Chen1
1College of Information Science and Engineering, Ocean University of China, Qingdao, Shandong Province, China.
PloS one
|October 24, 2023
概括
这项研究介绍了反响抑制网络 (RS-U-Net) 以减少水下声纳反响. 这种新型网络显著提高了回声信号的清晰度和在浅水中检测的准确性.
科学领域:
- 信号处理 信号处理
- 水下声学 水下声学
- 机器学习 机器学习
背景情况:
- 反响是主动声纳系统的主要干扰,特别是在浅水,降低目标检测.
- 反响抑制技术对于提高水下回声信号清晰度和准确性至关重要.
研究的目的:
- 提出一个端到端的网络,即反响抑制网络 (RS-U-Net),以有效地抑制水下声纳回声信号中的反响.
- 改进信号反响率 (SRR) 并提高在浅水环境中的目标检测精度.
主要方法:
- 一个端到端的网络架构RS-U-Net使用一维卷积网络 (1D-CNN) 进行特征提取.
- 该网络利用声纳回声信号数据作为输入,并采用自动编码器来初始化重量以优化训练时间和性能.
主要成果:
- RS-U-Net证明了有效抑制反响,改善了回声信号的信号反响比 (SRR).
- 实验验证显示,回声信号检测的改进约为10dB,优于现有方法.
- 与其他领先的技术相比,拟议的方法实现了大约2dB更好的反响抑制.
结论:
- RS-U-Net在浅水中的活跃声纳系统的反响抑制方面取得了重大进展.
- 网络架构和培训策略有效地提高了水下目标检测的性能和准确性.
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