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Dual-Band Multi-Channel Airborne Radar for Mapping the Internal and Basal Layers of Polar Ice Sheets
Marathe, Kiran Chidambara
Marathe, Kiran Chidambara
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Abstract
Rapid thinning of the Jakobshavn and a few other outlet glaciers in Greenland and the Antarctic has been observed in the past few years. The key to understanding these dramatic changes is basal conditions. None of the spaceborne radars, that have been providing a wealth of information about the ice surface, is capable of measuring ice thickness or mapping bed conditions. At the Center for Remote Sensing of Ice Sheets (CReSIS), we have developed an airborne radar system to map the internal and basal layers to obtain a 3-dimensional representation of the ice sheets in Polar Regions. We have also devised advanced signal processing techniques to overcome the effects of surface clutter. We have developed a radar for measuring ice thickness up to a 5000 m depth from low-altitude (500 m) and high-altitude (7000 m) aircraft. This airborne radar system can operate at two bands: very high frequency band (VHF-band) (140 MHz to 160 MHz) with a peak power of 800 W and P-band (435 MHz to 465 MHz) with a peak power of 1.6 kW for collecting data to develop effective ice sheet models. The pulse signal has a duration of 3 us or 10 us. The radar has 1 transmitter and 6 receivers inside the aircraft and an 8 element dipole antenna array mounted beneath the wings of the aircraft. This system is designed to have 32 coherent integrations and pulse compression due to which a high loop sensitivity of at least 208 dB was obtained. This system was tested and data were collected in the recent September 2007 field experiment over various parts of Greenland. From the initial observations of the collected data it can be deduced that the signal losses at 450 MHz are more than predicted by existing models and clutter masked the weak bed echoes when the data were collected at higher altitudes both at 150 MHz and 450 MHz.
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Date
2008-03-06
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University of Kansas
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Keywords
Electronics and electrical engineering, Remote sensing