Abstract
Abstract This paper reports the new concept of possibly applying independent component analysis (ICA) on Synthetic Aperture Radar (SAR) satellite images for separating atmospheric artifacts from effects due to topography and terrain displacements. Specifically, the FastICA algorithm is applied on simulations of SAR interferograms with the purpose of extracting the different independent sources. Results show the existence of significant correlations between estimated and original components, with correlation coefficients above 0.9 and statistical confidence level above 99.9%. These findings suggest that ICA might provide a useful tool in SAR data processing, with a specific crucial usefulness in cases of an absence of ground truth knowledge, as in the cases of insufficient meteorological information at specific observational times or in satellite monitoring of remote lands. Applications on real data show that the topographical component is automatically derived by the FastICA algorithm for whatever real data set. What is different is that the extraction of terrain displacements may require some a priori information for separating different kinds of landslides and that the use of possible semi-blind ICA/FastICA approach might be considered, dependent on the specific data set.
Highlights
Synthetic Aperture Radar (SAR) interferograms are obtained by analyzing two sets of radar images of the same areas with two slightly different viewing angles
This paper reports the new concept of possibly applying independent component analysis (ICA) on Synthetic Aperture Radar (SAR) satellite images for separating atmospheric artifacts from effects due to topography and terrain displacements
A realistic scenario of the interferometric phase differences between the corresponding pixels of two images taken at times TERRAPUB.instrumental noises:φ (tA) and TERRAPUB.instrumental noises:φ (tA)−φ (tB) can be expressed as the sum of components due to: (1) the topography, (2) the line-of-sight (LOS) cumulative deformations between the two times of the interferometric coupled images, (3) the atmospheric fluctuations, and (4) a random noise term which takes into account the temporal decorrelation due to random changes of the ground scatters for spatial scales of the order of signal wavelength or other random
Summary
Synthetic Aperture Radar (SAR) interferograms are obtained by analyzing two sets of radar images of the same areas with two slightly different viewing angles. The data for the coupled images can be obtained by two antennas located on the same platform (single-pass interferometry) or via repeated passes of the same sensor on two nearly parallel trajectories (repeated-pass interferometry). The latter is the most common situation in SAR processing, and it is always the case in any multi-satellite SAR interferometry (ERS-1/2, ERS-ENVISAT, RADARSAT or other). Because data acquisitions are not simultaneous in repeated-pass interferometry, there can be several sources of phase shifts due to slight differences in the viewing angle or satellite location and to the temporal fluctuations in the atmosphere and ground scatters. Further details on the applicability of ICA are presented in detail
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