Synthetic Aperture Radar Imaging Geometry Understanding And Processing

As an advanced Earth observation technology emerging in the 20th century, Synthetic Aperture Radar was broadly applied in the field of land cover mapping, ecology and agriculture, solid Earth science, hydrology, sea ice, because of its all weather day/night imaging capability and penetrating ground surface to some extent capability. In the future, Synthetic Aperture Radar will play a more important role in broader range, with the outcoming high resolution, multipolarization, multiband and optimal interferometry configuration.In China, SAR remote sensing technology has an extensively potential application market. Moreover, SAR maybe the only viable alternative for topography mapping in western China and topography map rapid updating in part of southern China characterized by persistent cloud-cover. But some issues concerning SAR geometric processing and radiometric calibration are not well resolved, which hinder this advanced technology from being applied on a large scale and being industrialized.The goal of this dissertation is to deal with the geometry-related issues and topography induced radiometric distortion in SAR images. On the basis of thorough and systematic analysis of geometric characteristics, the imaging equation of SAR images is developed, then, the issues concerning SAR geocoding, localization, image simulation, orbit precise determination by means of GCPs and terrain influences on backscatter and attempts to their correction. , are investigated in detail.In order to understanding SAR imagery profoundly, the principles of SAR forming process are formulated. How the pulse compression works and what is matching filter are analyzed in the viewpoint of signal processing. The Doppler frequency and its property are well addressed. The ultimate value of azimuth resolution and range resolution of SAR images are theoretically deduced. Then, the range ambiguity and azimuth ambiguity are considered.Imaging equation is the basis of geometric processing. After investigating the effect of Earth pertubatory forces on satellite orbits, a different parameters set describing orbit from I. Tannous et al (1994) and H. Rantakokko et al (1999) is proposed, which is the optimal trade-off between accuracy and computational simplicity. Then, the SAR imaging equation based on orbit parameters and SAR processor parameters are developed. SAR image geocoding, which is a transformation from object space to image plane, and SAR localization, which is a transformation from image plane to object space, consequently inversion of geocoding, are explored. The iterative algorithms to resolve localization and geocoding problem by means of imaging equation are presentedPrecise determination of SAR orbit is significant to SAR geocoding, as well as interferometric SAR processing and stereo SAR processing. A orbit refinement algorithm using ground control points is proposed, which linearizes the imaging equations and solve the orbit parameters under least square principle as space resection of aerophography.SAR simulation is a two-step process, one is geometric calculation of pixel position corresponding to DEM cell, and is similar with geocoding, the other is backscatter simulation. Frequently used backscatter models are reviewed. The difference between real and simulated images provides the control to refine orbit model. A hierarchical matching strategy between real and simulated SAR images is proposed and applied to automatic SAR geocoding.Terrain induced radiometric distortions have to be corrected when performing absolute radiometric calibration and relating backscatter with biomass, moisture and land cover classes. These distortions are categorized pixel scattering area effect and local incidence angle effect. To correct pixel scattering area effect, the area normalization factor is developed, to correct local incidence angle effect, a backscatter model formulated as a linear function of local incidence angle is presented, and then correction function. As an end, the correction algorithm of terrain induced radiometric distortions is developed.Last but not least, all the developed algorithms are programmed using c++. Utilizing ERS SLC data and RADARSAT SGF data, four tests are arranged, respectively about imaging equation based geocoding, orbit refinement using Ground Control Points, SAR simulation and its application to automatic geocoding, terrain induced radiometric distortion correction. The results of the tests are analyzed and concluded.