Abstract
AbstractEnglacial layers in Antarctica and Greenland are indicators of the dynamic, rheological and subglacial configuration of the ice sheets. Airborne radar sounder data is the primary remote sensing solution for directly observing englacial layers and structures at the glacier-catchment to ice-sheet scale. However, when traditional along-track synthetic aperture radar (SAR) processing is applied, steep layers can disappear, limiting the detectability and interpretability of englacial layer geometry. This study provides a reconstruction algorithm to address the problem of destructive phase interference during the radargram formation. We develop and apply a novel SAR processor optimized for layer detection that enhances the Signal-to-Noise ratio (SNR) of specular reflectors. The algorithm also enables the automatic estimation of layer slope. We demonstrate the algorithm using data acquired at the Institute Ice Stream, West Antarctica.
Highlights
Radar sounders are active sensors with nadir-looking geometries used for both Earth observation (Peters and others, 2007) and planetary science (Bruzzone, 2015)
We develop and apply a novel synthetic aperture radar (SAR) processor optimized for layer detection that enhances the Signal-to-Noise ratio (SNR) of specular reflectors
To assess the effectiveness of the proposed technique, we apply it to data acquired by the BAS PASIN instrument in the Institute and Möller Ice Stream region of West Antarctica during the 2010–2011 season
Summary
Radar sounders are active sensors with nadir-looking geometries used for both Earth observation (Peters and others, 2007) and planetary science (Bruzzone, 2015). In Holschuh and others (2014), the authors discussed this processing issue focusing on the quantification of power loss due to steeply dipping internal layers They show that coherent stacking of adjacent range lines reduces the SNR of non-horizontal layers. We avoid destructive summation among the reflected echoes by identifying and applying slope-specific phase corrections to adjacent signals within an aperture This has three important properties: (i) it allows the use of larger apertures and higher SNRs and more precise slope estimates than point-scatterer-based techniques, (ii) it recovers steep slopes (including those beyond PRF sampling limits) and (iii) it automatically extracts the slope of layers (including layers with along-track range variability smaller than a single range bin).
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