Signal Processing Techniques For Interferometric Synthetic Aperture Radar

Today, Interferometric Synthetic Aperture Radar, shortly termed InSAR or IfSAR, is an imaging technique for measuring the topography of a wide surface and its changes over time in nearly all weather conditions. A conventional SAR only measures the location of a target in a two-dimensional coordinate system, with one axis along the flight track ("along-track direction") and the other axis defined as the range from the SAR to the target ("cross-track direction"). Based on SAR systems, InSAR needs several observations over the same scene at different time or along different tracks, and with knowledge of the interferometer geometry, phase differences between the received signals can be converted into a digital elevation map or topography change map.This dissertation provides the process of signal processing for spaceborne cross-track (repeat-pass) interferometry, with emphysis on the key techniques of signal processing, such as image registration, phase filtering, and phase unwrapping.(1) Image registration. First, we coarsely register the master and slave SAR images from X-SAR real data by the cross-correlation algorithm; then perform the fine registration by the point projection algorithm based on the measurement of maximum frequency spectrum, with the consistency check employed by changing the the master and slave images and verifying the accuracy of a pair of control points.(2) Phase filtering. A locally adaptive directional filter is proposed for interferograms. It locates the directional window with local frequencies estimated, efficiently reducing phase noise, and takes the basic form of Lee adaptive complex filter to properly avoid losing the resolution of interferograms.(3) Phase unwrapping. Several effective phase unwrapping approaches are given in details.â‘ A synthetic phase unwrapping approach. The proposed approach, based on the branch-cut method and finite element method, obsorbs the advantages of the two methods, i.e., in a high-quality region, unwrapped phases retrieved by the branch-cut method are more accurate than those by the least-square method; in a low-quality region, the robustness of the least-square method is better than that of the branch-cut method.â‘¡A phase unwrapping approach based on the finite element method and local frequency estimation. Local frequency estimation multiplied by 2Ï€is substituted for a wrapped phase difference to reduce the bias of unwrapped phase gradients, and a solution to the phase unwrapping problem in a regular or irregular region can be easily found by the finite element method.â‘¢A region-growing phase unwrapping approach.