Speaker
Dr
Daniel Andre
(Cranfield University, DAC)
Description
Synthetic Aperture Radar (SAR) interferometry and Coherent Change Detection (CCD), both monostatic and bistatic, depend on high coherence between repeat pass SAR images pairs. In principle these approaches allow a sensitive change detection for example due to ground subsidence or due to vehicle tracks, both applications having clear civilian and military benefits.
However there is usually a difference in the radar collection geometry for the SAR image pair, which can lead to incoherence between SAR image pairs. When sensing flat terrain in a SAR-far-field regime, the incoherence due to collection geometry difference can be removed through a conventional global spatial frequency trimming process. However, it has been found that when the terrain either contains non-flat topography or is in a SAR-near-field regime, the optimal trimming process is substantially more involved, so much so that a per-pixel SAR bistatic back-projection imaging algorithm has been developed: Spatially Variant Incoherence Trimming (SVIT). The case where satellite illumination is collected bistatically via a ground based receiver would count as a SAR-near-field scenario.
The SVIT algorithm removes incoherent energy from the bistatic interferometric SAR image pair on a per-pixel basis according to the local radar geometry and topography, leaving a higher coherence SAR image pair as is evidenced by CCD products. In order to validate the approach, change detection measurements were conducted with GB-SAR, a Cranfield University ground-based radar system.
However, it is additionally noted that variation in bistatic Radar Cross-Section (RCS) from the ground is a factor that can lead to a loss of coherence between bistatic SAR collections. It is analytically shown that to improve SAR image coherence, bistatic polarimetric effects should be taken into account as they can lead to a significant change in RCS as a function of the changing bistatic geometry. Bistatic scattering in different polarimetric basis are calculated for a representative example scatterer over a full bistatic hemisphere of scattering geometries, indicating the receiver polarization necessary for maximising bistatic RCS and coherence.
The results indicate that for diffuse specular scattering ground, the bistatic polarimetric scattering response varies in a well-defined way, so that it is possible to develop an extension to previous spatially variant coherence improvement techniques, varying the bistatic polarization decomposition in a spatially variant manner to increase SAR coherence over the scene.
In order to accomplish this in the mountainous or SAR-near-field scenario, within the bistatic back projection image formation algorithm the appropriate bistatic polarimetric decomposition should be chosen for each radar pulse in the SAR aperture and for each SAR pixel: Spatially Variant Polarimetry (SVP). In general the appropriate basis will be different for the two SAR collections for which one wishes to improve coherence. For the flat ground and SAR-far-field scenario, the optimal approach reduces to a simpler approach of enhancement by adding linear combinations of polarimetrically decomposed whole SAR images.
Primary author
Dr
Daniel Andre
(Cranfield University, DAC)
Co-author
Dr
Keith Morrison
(Cranfield University)
