Characterizing Crevasse Clutter in Radar Sounding Data from Ice Sheets

Radar sounding, used to observe the englacial and subglacial conditions of ice sheets, has applications ranging from mapping paleo accumulation rates to predicting future sea level contributions. Orbital radar sounding would significantly improve our spatial and temporal coverage of ice sheets. However, understanding and resolving sources of radar clutter is essential to developing feasible orbital systems. Surface crevasses are a significant source of clutter that already limit the feasibility of airborne radar sounding in some of the fastest flowing and most rapidly changing regions of the ice sheet. While there are numerous documented examples of crevasse clutter in unprocessed data, a cogent model has not yet been developed to quantify how crevasse clutter strength changes with respect to the radars angle of incidence or the targets depth. Creating a mathematical model for crevasse clutter will allow us to better simulate radar sounding returns at different altitudes, frequencies, and bandwidths in order to understand the feasibility and requirements of new sounding technologies. We use multi-frequency unfocused airborne radar data collected by NASAs Operation IceBridge to empirically characterize the signatures of both isolated crevasses and crevasse fields. We estimate the crevasse signal-to-clutter ratio (SCR) by isolating the added signal strength of a crevasse along its hyperbolic path and comparing it to the uncluttered depth-power profiles. We then present estimates of crevasse SCR as a function of frequency, incidence angle, and depth and show how the SCR would scale with platform altitude. We also compare the SCR of unfocused and focused data to quantify how effective post-processing can be in suppressing crevasse clutter. Ultimately, these results can inform the development of mathematical models to predict the crevasse clutter returns received by a radar sounder.