Ground penetrating radar geologic field studies of the ejecta of Barringer Meteorite Crater, Arizona, as a planetary analog

Abstract

[1] Ground penetrating radar (GPR) has been a useful geophysical tool in investigating a variety of shallow subsurface geological environments on Earth. Here we investigate the capabilities of GPR to provide useful geologic information in one of the most common geologic settings of planetary surfaces, impact crater ejecta. Three types of ejecta are surveyed with GPR at two wavelengths (400 MHz, 200 MHz) at Meteor Crater, Arizona, with the goal of capturing the GPR signature of the subsurface rock population. In order to "ground truth" the GPR characterization, subsurface rocks are visually counted and measured in preexisting subsurface exposures immediately adjacent to and below the GPR transect. The rock size-frequency distribution from 10 to 50 cm based on visual counts is well described by both power law and exponential functions, the former slightly better, reflecting the control of fragmentation processes during the impact-ejection event. GPR counts are found to overestimate the number of subsurface rocks in the upper meter (by a factor of 2-3x) and underestimate in the second meter of depth (0.6-1.0x), results attributable to the highly scattering nature of blocky ejecta. Overturned ejecta that is fractured yet in which fragments are minimally displaced from their complement fragments produces fewer GPR returns than well-mixed ejecta. The use of two wavelengths and division of results into multiple depth zones provides multiple aspects by which to characterize the ejecta block population. Remote GPR measurement of subsurface ejecta in future planetary situations with no subsurface exposure can be used to characterize those rock populations relative to that of Meteor Crater.

The Moon’s farside shallow subsurface structure unveiled by Chang’E-4 Lunar Penetrating Radar

“…Despite the good quality of the radar image, the complexity of the spatial distribution and shape of the radar features makes identification of the geological structures/events that generated such features quite difficult (25). To overcome this problem, we applied a tomographic inversion algorithm (26) that is capable of gaining information about the size of the objects producing the radar features (scattering objects) when their dimension is larger than half of the signal wavelength (~0.2 m).…”

Selection of the InSight Landing Site

“…7.10) showed that the expected distribution has fewer rocks at large diameter (and small diameter) than a power law and more closely resembled the Rosin Rammler, Weibull, and exponential distributions that have been used previously to describe rock populations (Rosin and Rammler 1933;Gilvarry 1961;Gilvarry and Bergstrom 1961;Wohletz et al 1989;Brown and Wohletz 1995;Golombek and Rapp 1997;Golombek et al 2003bGolombek et al , 2008bGolombek et al , 2012bCraddock and Golombek 2016). Further, the exponential models developed by Golombek and Rapp (1997) are based on the area covered by rocks (or diameter squared), which results in a less curved distribution when translated into cumulative number distributions on a log-log plot than a true exponential (e.g., Golombek et al 2003bGolombek et al , 2008bGolombek et al , 2012bCraddock and Golombek 2016) that can be fit more readily to power law distributions over a limited diameter range (e.g., Grant et al 2006;Russell et al 2013). In addition, human observers in the pilot studies filtered out many large detections that are not rocks (mostly shadows from steep sided hills and scarps), such that automated fits of the model exponential distributions to just the rocks in the 1.5-2.25 m size range using the same process used for MSL (Golombek et al 2012b), accurately fit the observed rock distributions (Fig.…”

A Compressive Sensing-Based Approach to Reconstructing Regolith Structure from Lunar Penetrating Radar Data at the Chang’E-3 Landing Site

“…The capability of ground-penetrating radar (GPR) to penetrate different materials makes it an effective and nondestructive geophysical tool for mapping the subsurface stratigraphy of the Moon to a given depth, which depends on the radar frequency and dielectric property of the lunar surface materials [1,2]. For example, the Lunar Radar Sounder (LRS) onboard Kaguya was used to detect the geological structure at depths of 4-5 km under the lunar surface [3,4]; the Apollo Lunar Sounder Experiment (ALSE) on the Apollo 17 spacecraft obtained a large amount of geological data from depths of 1-2 km below the surface of Moon [4,5]; and the dual-frequency Lunar Penetrating Radar (LPR) on the Yutu lunar rover, part of China's Chang'E-3 (CE-3) lunar mission, focuses on mapping the near-surface stratigraphic structure of the lunar regolith to a depth of several tens of meters [2,4,[6][7][8].…”

“…For example, the hyperbolic signatures produced by these targets are small with respect to radar wavelength, whose axes and vertices are functions of their position and relative dielectric characteristics [16,17]. In the lunar regolith, the most common subsurface materials are fine-grained regolith and basalt debris [1,4], and the layered reflection is not obvious [7]. Moreover, there is extensive clutter and noise in LPR data images [15], such as the coupling between antennas and the lunar surface, electromagnetic interference, etc.…”