A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models.
A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models.
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DOI：
10.1080/00401706.2016.1274681
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Müller R
中科院分区：
文献类型：
--
作者：
Zhu H;Caspers P;Morris JS;Wu X;Müller R
声纳发出声音脉冲，并利用反射的回声来获得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。虽然现有的分析方法通常假设回声之间的独立性，但由于设备设置或实验设计，真实的声纳数据可能具有更复杂的结构。在本文中，我们认为声纳回波数据收集从多个地形基板的双通道声纳头。我们的目标是识别差分声纳对地形的响应，并研究这种双通道设计在区分目标方面的有效性。我们描述了一个统一的分析框架，严格地实现这些目标，同时，自动。通过将回波包络信号作为函数响应，将地形/信道信息作为函数回归设置中的协变量来进行分析。我们采用功能混合模型，便于估计地形和信道的影响，同时捕捉数据中的复杂层次结构。这个统一的分析框架结合了高斯模型和鲁棒模型。我们使用完整的贝叶斯方法拟合模型，这使我们能够在相同的建模框架下执行多个推理任务，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，并描述局部区域的区分能力。我们的声纳地形数据的分析确定的时间区域，反映差分声纳地形响应。判别分析表明，多通道或双通道设计实现的目标识别性能与单通道设计相当或更好。
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. While 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 paper, 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.
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DOI：
10.1080/01621459.2013.793118
发表时间：
2013-06-01
影响因子：
3.7
作者：
Martinez JG;Bohn KM;Carroll RJ;Morris JS
通讯作者：
Morris JS
影响因子：
2
作者：
Crainiceanu, Ciprian M.;Staicu, Ana-Maria;Ray, Shubankar;Punjabi, Naresh
通讯作者：
Punjabi, Naresh
影响因子：
2.4
作者：
Müller, R;Kuc, R
通讯作者：
Kuc, R
影响因子：
2.7
作者：
Kong, Dehan;Xue, Kaijie;Zhang, Hao H.
通讯作者：
Zhang, Hao H.
DOI：
10.1146/annurev-statistics-010814-020413
发表时间：
2015-01-01
期刊：
ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 2
影响因子：
--
作者：
Morris, Jeffrey S.
通讯作者：
Morris, Jeffrey S.