Marine Physical Laboratory, Scripps Institution of Oceanography, La Jolla, California 92093-0238, USA.
J Acoust Soc Am. 2012 Feb;131(2):1722-32. doi: 10.1121/1.3666012.
Environmental parameters can have large spatial and temporal variability in shelfbreak regions. The capability of sequential Bayesian filters in tracking this variation is investigated. Particle filtering (PF) is used to extract the environmental parameters and their uncertainties. The method tracks the environment with fewer particles relative to conventional geoacoustic inversion methods using successive independent inversions. As an example, data from the Shallow Water 2006 Experiment are processed. The PF approach first is used to track the source and the environment with little spatial variation just northwest of the shelfbreak. Then the strongly range-dependent shelfbreak region is analyzed and the PF results are compared to previous geoacoustic inversion studies from the region.
在陆架边缘区域，环境参数具有很大的空间和时间可变性。本文研究了序贯贝叶斯滤波器在跟踪这种变化方面的能力。粒子滤波（PF）用于提取环境参数及其不确定性。与使用连续独立反演的传统水声反演方法相比，该方法使用较少的粒子来跟踪环境。作为一个例子，处理了 2006 年浅海实验的数据。首先，PF 方法用于跟踪陆架边缘西北方向仅有少量空间变化的声源和环境。然后分析了强烈的距离相关陆架边缘区域，并将 PF 结果与该区域以前的水声反演研究进行了比较。
