ABSTRACT Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. Although existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this article, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. Supplementary materials for this article are available online.

中文翻译：

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使用贝叶斯函数混合模型对结构化声纳-地形数据进行统一分析

摘要 声纳发出声音脉冲并使用反射回波获取有关目标物体的信息。它为小型机器人平台提供了一种低成本、互补的传感模式。尽管现有的分析方法通常假设回波具有独立性，但由于设备设置或实验设计，真实声纳数据可能具有更复杂的结构。在本文中，我们考虑使用双通道声纳头从多个地形基底收集的声纳回波数据。我们的目标是确定对地形的差分声纳响应，并研究这种双通道设计在识别目标方面的有效性。我们描述了一个统一的分析框架，可以严格、同时和自动地实现这些目标。分析是通过将回波包络信号视为函数响应并将地形/通道信息视为函数回归设置中的协变量来完成的。我们采用功能混合模型，在捕获数据中复杂的层次结构的同时，有助于估计地形和通道效应。这个统一的分析框架结合了高斯模型和稳健模型。我们使用完整的贝叶斯方法拟合模型，这使我们能够在同一建模框架下执行多项推理任务，包括选择模型、估计感兴趣的影响、识别重要的局部区域、区分地形类型以及描述局部的判别力。地区。我们对声纳地形数据的分析确定了反映对地形的不同声纳响应的时间区域。判别分析表明，多通道或双通道设计实现了与单通道设计相当或更好的目标识别性能。本文的补充材料可在线获取。