Image Coregistration in Sar Interferometry

A critical procedure in Synthetic Aperture Radar (SAR) Interferometric (InSAR) processing was studied: SAR image coregistration. Two pairs of ERS-1/2 SAR tandem data, representing diverse terrain types and different baselines, were used in this research. The commonly used traditional SAR image coregistration algorithms were addressed and tested; the computationally intensive algorithms were examined; the results from those algorithms were compared, through the experiments carried out on real data. The results showed that the magnitude component had better performance compared to complex data for computing cross-correlation function. For fine coregistration, oversampling the cross-correlation function was more efficient than oversampling original SAR images and a factor of 10 was appropriate as the oversampling rate. A particular 4-parameter transformation was sufficient for subpixel coregistration of ERS SAR tandem data. The traditional resampling algorithms, nearest neighbour, bilinear, and cubic convolution, were tested and compared to the computationally intensive sinc interpolators with varied lengths. The most efficient sinc length was not always the longer one. The 2D sinc interpolation with windowing and modulation demonstrated the power of frequency preservation, but no evidence showed that the sinc produced better coherence than the common algorithms. The final InSAR DEM accuracy should be the ultimate standard for evaluating the best coregistration approaches.