| Summary: | This thesis describes the design and development of an HF-VHF autonomous, ground-based, ice-penetrating synthetic aperture radar for the monitoring of spatio-temporal changes in polar ice shelves. The introduction reviews physical and electromagnetic properties of ice sheets and ice shelves in the context of ice-penetrating radar systems. This is followed by a discussion of existing radar and autonomous rover platforms and the associated limitations in monitoring spatio-temporal changes with existing systems. Updated radio-frequency and mixed-signal processing circuitry are presented and compared against a prototype implementation. Limits on imaging performance are discussed in relation to the system performance and improvements for future iterations of the radar are recommended. A novel lightweight and broadband antenna design for use in polar environments is then presented. Improvements to the antenna performance based on measured results are quantified and developed using simulation tools, which are then validated against updated measurements from subsequent field trials. Degradations in radar performance related to the measured antenna behaviour are investigated through simulation and future considerations for improving the system performance are proposed. A two-dimensional modelling tool designed to reduce computational overheads in generating model datasets for the testing and validation of processing routines is developed, adopting a ray-solving procedure to determine the deramped FMCW signal arising from layered dielectric media and discrete reflection horizons. Modelled datasets of typical subglacial features are then used to describe the backprojection and frequency-wavenumber migration approaches to forming ground-based, synthetic aperture imaging. Finally, results from a field trial of the complete autonomous ground-based synthetic aperture radar on an Alpine glacier and a polar ice shelf are presented to validate the overall system performance. Synthetic aperture images from stop-and-go and ...
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