贝叶斯因子高频宽带主动声纳通过深度不变模式进行分辨扩张
Paul J Gendron1, Kenneth T Bowers1
1Department of Electrical and Computer Engineering, University of Massachusetts Dartmouth, Dartmouth, Massachusetts 02747, USA.
JASA express letters
|February 5, 2026
概括
一种新的贝叶斯因子主动声纳 (BFAS) 方法通过考虑深度不确定性和环境噪声来增强水下目标检测. 这种方法提高了信号与反射以及噪声比率,在复杂的环境中优于传统方法.
科学领域:
- 声学 声学 在声学上
- 信号处理 信号处理
- 海洋学 海洋学 海洋学
背景情况:
- 在水下环境中,主动声纳探测面临着折射介质和深度不确定性的挑战.
- 反响和噪声显著降低了检测性能,特别是在宽带波形和垂直阵列.
研究的目的:
- 开发一个强大的贝叶斯因子分辨器,用于在不确定的水下环境中进行主动声纳检测.
- 为了考虑到环境因素,如折射介质,反响和声纳检测中的深度不确定性.
主要方法:
- 构建一个贝叶斯因子歧视体,将环境信息和不确定性通过边缘化纳入其中.
- 贝叶斯因子活性声纳 (BFAS) 的开发,在光束延迟空间中使用时间变化的二次形式.
- 利用波导信息和深度不变模式用于多路径组合和最佳子空间平衡.
主要成果:
- 在最小平均风险的意义上,BFAS在目标,反响和噪声子空间中保持最佳平衡.
- 该方法通过结合多路径到达,有效地增加了信号与反响加噪声比,尽管目标深度不确定.
- 与单个镜面到达探测器相比,BFAS表现出优越的性能,即使具有完美的深度知识.
结论:
- 开发的贝叶斯因子活性声纳 (BFAS) 提供了一种强大而有效的方法,用于在深度不确定性的水下环境中检测散射物体.
- 由于BFAS能够利用多路径到达并考虑到环境复杂性,因此比传统的声纳检测技术具有显著的优势.
- 该方法在各种折射和浅水条件下显示出有希望的性能,验证了多路径组合策略.
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