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Distributed sensor array for bottom inversion

机译:分布式传感器阵列用于底部反转

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Seismic inversion with an AUV-based sensor array system is an appealing concept that opens up a number of interesting possibilities but faces also a number of technological and scientific challenges. Among the technological challenges there is the fact that sensor arrays are no longer hardwired to the tow ship and therefore on the fly data monitoring imposes stringent restrictions on the amount of data that can be sent to the support ship. One of the scientific challenges is to determine the optimal sensor array configuration by exploring AUV mobility for inverting the bottom geophysical structure of interest. In fact, the industry standard long planar array and the associated acoustic data processing may not be the setup with the highest performance for each scenario at hand. Generic optimization of sensor distribution through space has been a long standing problem to which there are no closed form solutions. Generically speaking, field diversity maximization is often referred to as a criteria for sensor positioning. This work explores data incoherence as a possible criteria to derive performance of distributed sensor arrays. Additional technological limitations such as array aperture, number of sensors and distances between vehicles impose additional constraints leading to suboptimal configurations. Compressed sensing array processing is used both to explore data incoherence and to offer data reduction for alleviating on the fly monitoring.
机译:基于AUV的传感器阵列系统的地震反转是一种吸引人的概念,开辟了许多有趣的可能性,但也面临着许多技术和科学挑战。在技​​术挑战中,传感器阵列不再将传感器阵列硬连线到牵引船,因此在飞行数据监视上对可以发送到支持船的数据量强加严格限制。其中一个科学挑战是通过探索AUV移动性来确定最佳传感器阵列配置,以反转底部地球物理结构。事实上,行业标准长平面阵列和相关的声学数据处理可能不是手掌中每个场景的最高性能的设置。通过空间的传感器分布的通用优化是一个长期存在的问题,没有封闭的形式解决方案。在晶体上讲,现场分集最大化通常被称为传感器定位的标准。这项工作探讨了数据不一致作为可能的标准,以导出分布式传感器阵列的性能。诸如阵列孔径,传感器数量和车辆之间的距离等附加技术限制施加了导致次优配置的额外约束。压缩传感阵列处理用于探索数据不一致,并为减少飞行监测提供数据减少。

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