Perspective Back-Projection Algorithm: Interface Imaging for Airborne Ice Detection
The deployment of traditional ground-penetrating radar (GPR) systems for ice detection on steep terrain presents substantial safety challenges for ground crews due to inaccessibility and hazardous working conditions. However, airborne GPR (AGPR) and radio echo sounding (RES) provide solutions to the...
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| Published in | Remote sensing (Basel, Switzerland) Vol. 17; no. 20; p. 3400 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Basel
MDPI AG
10.10.2025
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2072-4292 2072-4292 |
| DOI | 10.3390/rs17203400 |
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| Summary: | The deployment of traditional ground-penetrating radar (GPR) systems for ice detection on steep terrain presents substantial safety challenges for ground crews due to inaccessibility and hazardous working conditions. However, airborne GPR (AGPR) and radio echo sounding (RES) provide solutions to these difficulties. Assuming that ice is homogeneous, we introduce a perspective back-projection algorithm designed to process AGPR or RES data that directly searches for unobstructed refracted electromagnetic (EM) wave paths and focuses EM energy below the surface by computing path-specific travel times. The results from the 2D and 3D imaging tests indicate that the perspective back-projection algorithm can accurately image the ice–rock interface. However, Snell’s Law suggests that part of the energy may fail to propagate through the air–ice interface and reach either the ice–rock interface or the receivers in scenarios where the incident angle of an EM wave exceeds a certain threshold. This energy deficit can hinder the perspective back-projection algorithm from accurately imaging such ice–rock interfaces. Despite these limitations, the perspective back-projection algorithm remains a promising tool for imaging sub-ice interfaces in AGPR and RES ice detection. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2072-4292 2072-4292 |
| DOI: | 10.3390/rs17203400 |