海洋环境噪声的参数化使用直角分解
Gleb Panteleev1, Max Yaremchuk1, W Erick Rogers1
1U.S. Naval Research Laboratory, Stennis Space Center, Mississippi 39529, USA.
The Journal of the Acoustical Society of America
|March 20, 2025
概括
经验直角函数 (EOF) 分解有效处理和预测海洋环境噪声,解释高达98%的频谱. EOF提高了空隙填充的准确性,并实现了高效,连续的噪音预测.
科学领域:
- 海洋学 海洋学 海洋学
- 声学 声学 在声学方面
- 数据分析 数据分析
背景情况:
- 开放海洋中的环境噪音对于各种海洋应用至关重要.
- 处理和预测海洋噪声的传统方法面临数据缺口和异常值的挑战.
研究的目的:
- 评估经验直角函数 (EOF) 分解对于处理和预测公海环境噪声的实用性.
- 评估基于EOF的方法,用于填补数据缺口和噪声频谱预测.
主要方法:
- 实证直角函数 (EOF) 分解应用于南大洋环境噪声观测.
- 单值分解 (SVD) 用于分析和预处理噪声数据.
- 基于EOF的空白填补与线性插值的比较.
主要成果:
- 前三个EOF分别解释了89%,96%和98%的环境噪声频谱.
- 基于EOF的空白填充实现了比线性插值大约35%更高的准确性.
- EOFs减少了噪声预测的回归参数,使得计算效率高,连续频谱预测.
结论:
- EOF分解是分析和预测海洋环境噪声的强大工具.
- 基于EOF的方法在数据处理和预测准确性方面提供了显著的改进.
- 准确预测频率平均噪声大小是提高光谱预测准确性的关键.
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