Joint Estimation of Ice Sheet Vertical Velocity and Englacial Layer Geometry from Multipass Synthetic Aperture Radar Data

Ice dynamics are a major factor in sea level rise and future sea-level rise projections [1]. The vertical velocity profile of the ice is one major knowledge gap in both observations and model experiments. We propose to apply multipass differential interferometric synthetic aperture radar (DInSAR) techniques to data from the Multichannel Coherent Radar Depth Sounder (MCoRDS) to measure the vertical displacement of englacial layers. Estimation of englacial layer vertical displacement requires compensating for the spatial baseline between interferometric antenna pairs using radar trajectory information and estimates of the cross-track layer slope from direction of arrival (DOA) analysis, but airborne systems suffer from unknown spatial baseline errors. The current DInSAR algorithm assumes zero error in the array position information when inferring displacement and the direction of arrival for subsurface scatterers, which means that unincorporated baseline errors map into errors in cross-track slope and vertical velocities. Here we demonstrate a maximum likelihood estimator that jointly estimates the vertical velocity, the cross-track internal layer slope, and the unknown baseline error due to GPS and Inertial Navigation System (INS) errors.