With meter-resolution images delivered by modern SAR satellites like TerraSAR-X and TanDEM-X, it is now possible to map urban areas from space in very high level of detail using advanced interferometric techniques such as {PSI} and ({SAR} Tomography) {TomoSAR}, whereas these multi-pass interferometric techniques are based on a great number of images. We are aiming at improving the estimation accuracy of {TomoSAR} while reducing the required number of images. In the paper, we propose a novel workflow that marries the freely available 2D building footprint {GIS} data and the group sparsity concept for {TomoSAR} inversion. Experiments on bistatic {TanDEM}-X data stacks demonstrate the great potential of the proposed approach.
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With meter-resolution images delivered by modern SAR satellites like TerraSAR-X and TanDEM-X, it is now possible to map urban areas from space in very high level of detail using advanced interferometric techniques such as {PSI} and ({SAR} Tomography) {TomoSAR}, whereas these multi-pass interferometric techniques are based on a great number of images. We are aiming at improving the estimation accuracy of {TomoSAR} while reducing the required number of images. In the paper, we propose a novel work...
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