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Bayesian mass anomaly estimation with measurements of gravity

机译:利用重力测量进行贝叶斯质量异常估计

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The paper describes the implementation of a Bayesian model to assess novel gravimeters and gradiometers, which employ recent advances in cold matter wave interferometry to accurately measure micro-gravity. This has application to the resolution of underground structures, as an array of measurements at the surface can be used to infer what lies beneath. Potential applications of this technology include: improved identification of oil reservoirs; the detection of sink-holes to support civil engineering; detection of underground buildings; and geophysical mapping as a means to navigate in GPS denied environments. For the challenge of detecting underground voids at depths 10m beneath the Earth, the utility of the posterior distribution for computing probability of excavation maps is described and the impact of different sampling configurations and densities is investigated.
机译:本文介绍了贝叶斯模型的实现,以评估新颖的重力计和梯度计,它们利用冷物质波干涉法的最新进展来精确测量微重力。这适用于地下结构的分辨率,因为可以使用地面上的一系列测量值来推断其下方的内容。该技术的潜在应用包括:改进对油藏的识别;检测下沉孔以支持土木工程;检测地下建筑物;和地球物理测绘作为在GPS被拒绝的环境中导航的一种手段。为了检测在地球下方10m处的地下空隙所面临的挑战,描述了后验分布用于计算挖掘图概率的效用,并研究了不同采样配置和密度的影响。

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