Culver R Lee, Camin H John
Applied Research Laboratory and Graduate Program in Acoustics, The Pennsylvania State University, State College, Pennsylvania 16804, USA.
J Acoust Soc Am. 2008 Dec;124(6):3619-31. doi: 10.1121/1.3006379.
Acoustic signals propagating through the ocean are refracted, scattered, and attenuated by the ocean volume and boundaries. Many aspects of how the ocean affects acoustic propagation are understood, such that the characteristics of a received signal can often be predicted with some degree of certainty. However, acoustic ocean parameters vary with time and location in a manner that is not, and cannot be, precisely known; some uncertainty will always remain. For this reason, the characteristics of the received signal can never be precisely predicted and must be described in probabilistic terms. A signal processing structure recently developed relies on knowledge of the ocean environment to predict the statistical characteristics of the received signal, and incorporates this description into the processor in order to detect and classify targets. Acoustic measurements at 250 Hz from the 1996 Strait of Gibraltar Acoustic Monitoring Experiment are used to illustrate how the processor utilizes environmental data to classify source depth and to underscore the importance of environmental model fidelity and completeness.
在海洋中传播的声信号会被海洋水体及其边界折射、散射和衰减。海洋对声传播的影响在很多方面是已知的，因此通常可以在一定程度上确定地预测接收信号的特征。然而，海洋声学参数会随时间和地点变化，其变化方式无法精确得知，也永远不可能精确得知；总会存在一些不确定性。因此，接收信号的特征永远无法精确预测，而必须用概率术语来描述。最近开发的一种信号处理结构依赖于海洋环境知识来预测接收信号的统计特征，并将这种描述纳入处理器中，以便检测和分类目标。利用1996年直布罗陀海峡声学监测实验中250赫兹的声学测量数据来说明处理器如何利用环境数据对声源深度进行分类，并强调环境模型保真度和完整性的重要性。
