Morrison, K.
ORCID: https://orcid.org/0000-0002-8075-0316 and Bennett, J. C.
(2015)
Virtual bandwidth SAR (VB-SAR) for centimetric-scale sub-surface imaging from space.
International Journal of Remote Sensing, 36 (7).
pp. 1789-1808.
ISSN 0143-1161
doi: 10.1080/01431161.2015.1025922
Abstract/Summary
Virtual bandwidth synthetic aperture radar (VB-SAR) is a radical new technique that promises, for the first time, sub-surface imaging at large stand-off distances applicable to airborne and spaceborne platforms. The scheme relies on understanding and exploiting the way a radar wave interacts with a soil volume. A wave passing through a soil to a buried object is delayed relative to the equivalent free-space path due to the higher relative permittivity of a soil, which is measured as a phase shift. This can equivalently be thought of as a shift in the real radar frequency to a virtual frequency. Temporal variations in soil moisture across a temporal stack of differential interferometric SAR (DInSAR) images can transport the real radar frequency at a pixel across a set of virtual frequencies to create a virtual bandwidth. Even small changes in moisture can produce large virtual bandwidths promising very high, centimetric-scale vertical resolutions: 1.6 cm at X-band and 8.6 cm at L-band for a 10% moisture change in a sandy soil. To produce a sub-surface depth profile at an image pixel, a Fourier transform is performed on the complex data stack collected across the DInSAR set. Retrieving the depth profile at each pixel across the 2D image provides a 3D map of the sub-surface backscattering through the scene. A description of the model is presented, and representative modelling results are presented to assess performance and application across different soil types, moisture regimes, and SAR platforms.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/73531 |
| Identification Number/DOI | 10.1080/01431161.2015.1025922 |
| Refereed | Yes |
| Divisions | Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology |
| Publisher | Taylor & Francis |
| Download/View statistics | View download statistics for this item |
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