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Abstract

Synthetic aperture radar (SAR) interferometry is a technique for obtaining accurate elevation maps of the Earth from radar images. Local fringe frequency estimates are needed in several stages of the interferometry process. They are used to correct the effect of the topographic slope in the estimation of the interferogram coherence. They are needed to define the frequency center for adaptive band-pass filtering or to model the local phase in slope-correction filtering. Finally, accurate fringe frequency estimates facilitate the phase unwrapping process. In this work, I propose a new algorithm for local fringe frequency estimation in which the SAR interferogram signal is pre-filtered before the local frequency estimation is performed. This allows the use of a simpler and more efficient frequency estimator that operates at the pixel level. The proposed scheme shows advantages over other schemes because it achieves a better spacefrequency resolution and therefore tracks the topographic changes of the scene more accurately. The filters used in this work are modulated Gaussian functions with variable spatial aperture and bandwidth. In this way, the analysis window is adapted to the local characteristics of the signal at all samples. The variable-aperture filters are similar to the variable space-frequency domain filters used in wavelet analysis. I present results for synthetic and real SAR interferograms, as well as the performance of the proposed algorithm. An application of the frequency estimation method is developed for the noise filtering stage. A non-linear phase model is built to locally flatten the phase allowing the averaging of a higher number of samples without significant distortion. Simulations show that this alternative method achieves a better performance than two other reported methods when the interferogram coherence is moderately high. However, the alternative method does not solve the problem of phase discontinuities in the presence of topographically induced residues.