This article presents a technique for the determination of the relative misregistration between two interferometric SAR images. The proposed technique is based on the spectral properties of the complex SAR signal. Unlike conventional coregistration methods, the proposed technique does not need any interpolation nor cross-correlation procedures and also no coherence or fringe optimization must be performed. Instead, the phase information of different spectral looks is evaluated giving misregistration information on a pixel by pixel basis. The proposed technique is at least as accurate as the conventional algorithms and its implementation is very simple. Airborne repeat-pass interferometric data and simulated ScanSAR data are used to illustrate the operation of the proposed technique.

During the last decade, synthetic aperture radar (SAR) became an indispensable source of information in Earth observation. This has been possible mainly due to the current trend toward higher spatial resolution and novel imaging modes. A major driver for this development has been and still is the airborne SAR technology, which is usually ahead of the capabilities of spaceborne sensors by several years. Today's airborne sensors are capable of delivering high-quality SAR data with decimeter resolution and allow the development of novel approaches in data analysis and information extraction from SAR. In this paper, a review about the abilities and needs of today's very high-resolution airborne SAR sensors is given, based on and summarizing the longtime experience of the German Aerospace Center (DLR) with airborne SAR technology and its applications. A description of the specific requirements of high-resolution airborne data processing is presented, followed by an extensive overview of emerging applications of high-resolution SAR. In many cases, information extraction from high-resolution airborne SAR imagery has achieved a mature level, turning SAR technology more and more into an operational tool. Such abilities, which are today mostly limited to airborne SAR, might become typical in the next generation of spaceborne SAR missions.

This paper presents results on SAR interferometry for data acquired in the Terrain Observation by Progressive Scans (TOPS) imaging mode. The rationale to retrieve accurate interferometric products in this mode is expounded, emphasizing the critical step of coregistration. Due to the particularities of the TOPS mode, a high Doppler centroid is present at burst edges, demanding a very high azimuth coregistration performance. A coregistration accuracy of around one tenth of a pixel, as it is usually recommended for stripmap interferometric data, could result in large undesired azimuth phase ramps in each TOPS burst. This paper presents two approaches based on the spectral diversity technique to precisely estimate this coregistration offset with the required accuracy and evaluates their performance. The effect of squint at burst edges in terms of an undesired impulse response shift during focusing and the impact on the interferometric coregistration performance is also addressed. Repeat-pass TOPS data acquired experimentally by TerraSAR-X are used to validate the proposed approaches.

This paper presents an efficient phase preserving processor for the focusing of data acquired in sliding spotlight and Terrain Observation by Progressive Scans (TOPS) imaging modes. They share in common a linear variation of the Doppler centroid along the azimuth dimension, which is due to a steering of the antenna (either mechanically or electronically) throughout the data take. Existing approaches for the azimuth processing can become inefficient due to the additional processing to overcome the folding in the focused domain. In this paper, a new azimuth scaling approach is presented to perform the azimuth processing, whose kernel is exactly the same for sliding spotlight and TOPS modes. The possibility to use the proposed approach to process data acquired in the ScanSAR mode, as well as a discussion concerning staring spotlight, is also included. Simulations with point targets and real data acquired by TerraSAR-X in sliding spotlight and TOPS modes are used to validate the developed algorithm.

This paper presents the first fully polarimetric high-resolution circular synthetic aperture radar (CSAR) images at L-band (1.3 GHz). The circular data were acquired in 2008 by the Experimental SAR (E-SAR) airborne system of the German Aerospace Center (DLR) over the airport of Kaufbeuren, Germany. The obtained images resulting from the coherent integration of the whole circular flight are investigated and discussed in terms of two of the main CSAR properties, namely, the theoretical subwavelength resolution in the horizontal plane (x, y) and the 3-D imaging capabilities. The 3-D imaging capabilities are of special interest due to the penetration of L-band in vegetated areas. These results were compared with images processed by the incoherent addition of the full synthetic aperture. The coherent approach showed a better performance since scatterers are focused at their maximum resolution. Due to the nonlinearity of the tracks and the high-computational burden, an efficient fast factorized back-projection (FFBP) has been developed. Unlike frequencydomain processors, it accommodates azimuthal variances and topography changes. Limits and considerations of the proposed algorithm are described and discussed. To further accelerate this process, the FFBP was also implemented in a graphics processing unit (GPU). Processing performance has been assessed with the direct BP (DBP) as a reference, obtaining speedup factors up to 1800. Residual motion errors have been estimated with a new frequency-based autofocus approach for CSAR configurations based on low signal-to-clutter ratio (SCR) isotropic scatterers. High-resolution images of man-made and distributed scatterers have been analyzed and compared with a stripmap SAR, both concerning anisotropic and isotropic-like scatterers. Results include a single-channel tomogram of a Luneburg lens and a fully polarimetric tomogram of a tree.