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Continuous monitoring of the lunar or Martian subsurface using on-board pattern recognition and neural processing of Rover geophysical dataThe ultimate goal is to create an extraterrestrial unmanned system for subsurface mapping and exploration. Neural networks are to be used to recognize anomalies in the profiles that correspond to potentially exploitable subsurface features. The ground penetrating radar (GPR) techniques are likewise identical. Hence, the preliminary research focus on GPR systems will be directly applicable to seismic systems once such systems can be designed for continuous operation. The original GPR profile may be very complex due to electrical behavior of the background, targets, and antennas, much as the seismic record is made complex by multiple reflections, ghosting, and ringing. Because the format of the GPR data is similar to the format of seismic data, seismic processing software may be applied to GPR data to help enhance the data. A neural network may then be trained to more accurately identify anomalies from the processed record than from the original record.
Document ID
19910015929
Acquisition Source
Legacy CDMS
Document Type
Other
Authors
Mcgill, J. W. (Arizona Univ. Tucson, AZ, United States)
Glass, C. E. (Arizona Univ. Tucson, AZ, United States)
Sternberg, B. K. (Arizona Univ. Tucson, AZ, United States)
Date Acquired
September 6, 2013
Publication Date
January 1, 1990
Publication Information
Publication: NASA Space Engineering Research Center for Utilization of Local Planetary Resources
Subject Category
Lunar And Planetary Exploration
Accession Number
91N25243
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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