Unattended Ground Sensing and In-Situ Processing of Geophysical Data
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Active source seismic data was collected at the Nevada National Security Site using the Seismic Hammer(TM) (SH), under contract from HK Exploration. The SH generates a seismic pulse by dropping a 13 metric ton mass from a height of 1.5 m. Post-survey evaluation of collected data revealed inconsistencies in shot trigger time that required additional analysis and correction using cross-correlation and/or time shifts derived from manual picks of trigger times. While the primary analysis for which this data set was collected is independent of the knowledge of shot trigger time, other processing methods require highly precise knowledge of the trigger time. In order to make the Thor data set more usable to the larger community, additional work was undertaken. Results using the preferred method of cross-correlation were found to be satisfactory. An improved timing fiducial approach is required to reduce timing errors.
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The goal of this LDRD was to demonstrate the use of robotic vehicles for deploying and autonomously reconfiguring seismic and acoustic sensor arrays with high (centimeter) accuracy to obtain enhancement of our capability to locate and characterize remote targets. The capability to accurately place sensors and then retrieve and reconfigure them allows sensors to be placed in phased arrays in an initial monitoring configuration and then to be reconfigured in an array tuned to the specific frequencies and directions of the selected target. This report reviews the findings and accomplishments achieved during this three-year project. This project successfully demonstrated autonomous deployment and retrieval of a payload package with an accuracy of a few centimeters using differential global positioning system (GPS) signals. It developed an autonomous, multisensor, temporally aligned, radio-frequency communication and signal processing capability, and an array optimization algorithm, which was implemented on a digital signal processor (DSP). Additionally, the project converted the existing single-threaded, monolithic robotic vehicle control code into a multi-threaded, modular control architecture that enhances the reuse of control code in future projects.