EAGER: Development of Remote Sensing of Seismological Signals via the Enhanced Moiré Technique

火山学家使用各种传感器来监测火山活动，主要依靠地震仪记录地下岩浆运动的信号。然而，由于火山建筑物高度衰减和散射地震波，除非有密集的地震仪网络，否则关键的地震信号可能无法记录。在许多火山地区，由于后勤和/或环境的限制，不可能使用传统的地震仪部署这样的网络;例如靠近活火山口的地区无法进入。现有的地震信号遥感技术在安全性和分辨率方面都有局限性。在这个EAGER项目中，将利用增强的莫尔技术开发一种新的遥感技术。当两个类似的直线图案（称为光栅）重叠并相对于彼此旋转一个小角度时，就会产生莫尔图案。光栅的小位移（即，直线图案）通过莫尔图案被放大，因此可以精确地测量。在这种方法中，一个光栅由无人机放置在远程位置，另一个放置在基站的望远镜内。因此，可以远程记录远程位置的位移（振动）。阻碍这种方法遥感地震信号能力的主要挑战是大气湍流的存在，它可能在记录的信号中产生显著的噪声。为了应对这一挑战，将开发先进的预处理和后处理技术，并对远程记录的地震信号进行数值测试，以评估该方法在各种大气条件下测量地面位移的准确性。该方法是莫尔技术的增强，莫尔技术对直线网格之间的差分运动产生的图案进行成像。在我们的例子中，其中一个网格由无人机放置在远程位置，另一个放置在基础望远镜内。这种技术可以测量微小的地面位移，但由于大气湍流而受到信号衰减的影响。我们将开发预处理和后处理技术，以减少湍流的影响。光学预处理器将使用一种称为主动卷积照明（ACI）的新型变形/噪声抑制方案，其中使用电介质超表面系统地修改图像光谱。在这里，使用数值模拟，ACI的性能，以减少大气湍流的影响将进行评估。虽然ACI工作将测试显着增强数据采集的可行性，但将开发基于深度学习和小波包分解方法（DL-WPD）的后处理程序并应用于数据，以进一步提高地震测量的准确性。如果成功的话，这种新的遥感技术将通过在其他无法到达的地区进行地震记录来提高我们对火山过程的了解。此外，由于地震学是预测火山爆发和减轻相关危害的重要工具，新仪器将直接造福社会。此外，其他学科，如地震地震学，土木和机械工程可以采用所提出的方法，以获得高质量的地震信号的各种应用。这个奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用该基金会的智力价值和更广泛的影响审查标准。

Volcanologists use a variety of sensors to monitor volcanic activities, relying heavily on seismometers to record signals from subsurface magma movement. However, because volcanic edifices highly attenuate and scatter seismic waves, critical seismic signals may go unrecorded unless a dense network of seismometers is available. In many volcanic areas, it is impossible to deploy such a network using conventional seismometers due to logistic and/or environmental limitations; such as areas close to an active volcanic crater being inaccessible. Existing techniques for remote sensing of seismic signals have safety or resolution limitations. In this EAGER project, a new remote sensing technique will be developed using the enhanced Moiré technique. Moiré patterns are produced when two similar straight-line patterns (called gratings) are overlaid and rotated relative to each other by a small angle. Small displacement of the grating (i.e., straight -line patterns) is magnified through the Moiré patterns, and hence can be measured accurately. In this approach, one grating is placed by a UAV in the remote location and the other within a telescope in the base station. Thus, the displacements (vibrations) of the remote location can be recorded remotely. The major challenge that hampers the ability of this method for the remote sensing of seismic signals is the presence of atmospheric turbulence that can create significant noise within the recorded signals. To address this challenge advance pre- and postprocessing techniques will be developed and numerically tested on the remotely recorded seismic signals to assess the accuracy of the method to measure ground displacements for various atmospheric conditions.A new remote sensing technique will be developed for measuring seismic waves. The approach is an enhancement of the Moiré technique, which images the patterns produced by differential motion between straight-line grids. In our case, one of the grids is placed on a remote location by a UAV and the other, within a base telescope. This technique can measure minuscule ground displacement but is subject to signal degradation due to atmospheric turbulence. We will develop both pre- and postprocessing techniques to reduce the effect of turbulence. The optical preprocessor will use a novel and transformative distortion/noise suppression scheme called active convolved illumination (ACI), in which the image spectrum is systematically modified using dielectric metasurfaces. Here, using numerical simulations, the performance of ACI to reduce the effect of the atmospheric turbulence will be assessed. While the ACI work will test the feasibility of significantly enhanced data acquisition, a postprocessing procedure based on the deep learning and wavelet packet decomposition method (DL-WPD) will be developed and applied to the data to further enhance the accuracy of seismological measurements. If successful, this new remote sensing technique will improve our understanding of volcanic processes by enabling seismic recording in otherwise inaccessible areas. In addition, because seismology is an essential tool for forecasting volcanic eruptions and mitigating the associated hazards, the novel instrument will directly benefit society. Moreover, other disciplines such as earthquake seismology, and civil and mechanical engineering can adopt the proposed method to obtain high-quality seismic signals for a variety of applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.