Abstract

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.

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