准确的深度图:通过波形扩散模型为水下声学目标准确的动态暗频线回收
Ziyuan Xiao1,2, Yina Han1,2, Zihao Guo1,2
1School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
The Journal of the Acoustical Society of America
|December 18, 2025
概括
这项研究引入了一种新的波形扩散模型,用于水下源的识别. 该模型有效地恢复动态暗频线路,即使信号噪声比较低,提高遥感准确度.
科学领域:
- 信号处理 信号处理
- 遥感 遥感 遥感 遥感
- 机器学习 机器学习
背景情况:
- 精确的频线估计对于在遥感中对水下源的分类至关重要.
- 挑战包括低信号噪声比 (SNR),频率变化和不可预测的信号出生/死亡时间.
研究的目的:
- 开发一种改进的方法,用于在遥感中进行动态暗频线回收.
- 通过考虑频率线和背景噪声来解决现有方法的局限性.
主要方法:
- 建议采用波形扩散模型,包括频线和背景噪声.
- 前进过程:逐渐添加高斯噪声以创建具有不同SNR的信号.
- 反向过程:训练模型预测和去除添加的噪声,通过多变量高斯噪声来建模非高斯噪声.
主要成果:
- 该模型成功地处理模拟和现实数据集之间的波动和直线频率线.
- 在动态模糊线回收中实现卓越的性能,即使在低SNR.
- 有效地识别低SNR的信号出生和死亡时间点.
结论:
- 拟议的波形扩散模型在具有挑战性的遥感场景中为水下源识别提供了强大的解决方案.
- 该方法在检测微弱信号及其时间特征的准确性和能力方面取得了显著的改进.
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