Two-Dimensional Phase Unwrapping fo SAR Interferograms by Charge Connection Through Neutral Trees
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It is well established that interferometric synthetic aperture radar (SAR) images can be inverted to perform surface elevation mapping. Among the factors critical to the mapping accuracy are registration of the interfering SAR images and phase unwrapping. A novel registration algorithm is presented that determines the registration parameters through optimization. A new figure of merit is proposed that evaluates the registration result during the optimization. The phase unwrapping problem is approached through a new method involving fringe line detection. The algorithms are tested with two SEASAT SAR images of terrain near Yellowstone National Park. These images were collected on Seasat orbits 1334 and 1420, which were very close together in space, i.e., less than 100 m. The resultant elevation map is compared with the USGS digital terrain elevation model.
Methods are presented for using Synthetic Aperture Radar (SAR) interferometry data to estimate surface topography. An expression is given to relate the elevation of a ground point to the phase difference of SAR images received from two spatially separated antennas. An iterative algorithm which solves for the position and elevation of each point in the image simultaneously is developed. One of the critical issues that determines the accuracy of the terrain mapping is the phase unwrapping. An approach to the problem by fringe line detection is proposed. The algorithms are tested with two Seasat SAR images of terrain near Yellowstone National Park. The resultant elevation map is compared with a USGS terrain elevation model. The error of the SAR elevation with respect to the digital terrain map is about 8.2 percent of the total terrain variation.
Interferometric Synthetic Aperture Radar (IFSAR) is a technique that allows an automated way to carry out terrain mapping. IFSAR is carried out by first generating a SAR image pair from two antennas that are spatially separated. The phase difference between the SAR image pair is proportional to the topography. After registering the SAR images, the difference in phase in each pixel is extracted to generate an interferogram. Since the phase can only be measured within 2pi radians, phase unwrapping is carried out to extract the absolute phase for each pixel that will be proportional to the local height. While IFSAR algorithm is typically applied to measurement data, it is useful to develop an IFSAR simulator to develop a better understanding of the IFSAR technique. The IFSAR simulator can be used in choosing system parameters, experimenting with processing procedures and mission planning. In this paper we will present an IFSAR simulation methodology to simulate the interferogram based on the shooting and bouncing ray (SBR) technique. SBR is a standard ray-tracing technique used to simulate scattering from large, complex targets. SBR is carried out by shooting rays at the target or scene. At the exit point of each ray, a ray-tube integration is done to find its contribution to the total field. A fast algorithm has been developed for the SBR for simulating SAR images of complex targets. In the IFSAR simulation, we build upon the fast SAR simulation technique. Given the antenna pair configuration, radar system parameters and the geometrical description of the scene, we first simulate two SAR images from each antenna. After post processing the two SAR images, we generate an interferogram. Phase unwrapping is then performed on the interferogram to arrive at the desired terrain map. We will present results from the SBR-based IFSAR simulator. The results will include terrain map reconstruction of urban environments. The reconstruction will be compared to the ground truth to examine the fidelity of the simulation. We will also investigate the effect of multi-bounce scattering in urban environments on phase unwrapping and reconstruction.
A new algorithm for the direct calculation of topographic slope maps from synthetic aperture radar (SAR) interferograms is presented. The algorithm derives slope maps without first requiring the creation of a digital elevational model (DEM) from the interferogram, thus obviating the need for high SNR in the interferogram and altitude calibration points for the scene. SAR data useful for interferometry has been collected by the Active Microwave Imager on board the ERS-1 satellite, when it was in a short period repeat orbit. Two passes of the radar sensor form a cross-track interferometric baseline. For a point target at some position (x,y,h), the interferometric phase difference phi is proportional to the difference in path lengths for the two sensor positions to the scatterer. Given the phase difference as measured in the complex interferogram and an accurate baseline geometry, the position of the scatterer, most significantly the height h, can be determined through triangulation. The interferometric phase measurement however is known only modulo 2-pi, and hence it is necessary to determine the correct multiple of 2-pi to add to the phase at each point to obtain an estimate of the actual phase with respect to an absolute datum. This phase unwrapping process is required for creating DEM's, and is difficult or impossible for regions of low SNR or SAR image layover. The new algorithm described here derives slope maps without requiring phase unwrapping.
Jurassicprok is a computer program that generates strip-map digital elevation models and other data products from raw data acquired by an airborne synthetic-aperture radar (SAR) system. This software can process data from a variety of airborne SAR systems but is designed especially for the GeoSAR system, which is a dual-frequency (P- and X-band), single-pass interferometric SAR system for measuring elevation both at the bare ground surface and top of the vegetation canopy. Jurassicprok is a modified version of software developed previously for airborne-interferometric- SAR applications. The modifications were made to accommodate P-band interferometric processing, remove approximations that are not generally valid, and reduce processor-induced mapping errors to the centimeter level. Major additions and other improvements over the prior software include the following: a) A new, highly efficient multi-stage-modified wave-domain processing algorithm for accurately motion compensating ultra-wideband data; b) Adaptive regridding algorithms based on estimated noise and actual measured topography to reduce noise while maintaining spatial resolution; c) Exact expressions for height determination from interferogram data; d) Fully calibrated volumetric correlation data based on rigorous removal of geometric and signal-to-noise decorrelation terms; e) Strip range-Doppler image output in user-specified Doppler coordinates; f) An improved phase-unwrapping and absolute-phase-determination algorithm; g) A more flexible user interface with many additional processing options; h) Increased interferogram filtering options; and i) Ability to use disk space instead of random- access memory for some processing steps.