Subaperture Motion-Adaptive Reconstruction Techniques for Digital Beamforming Airborne SAR

Abstract

The use of airborne synthetic aperture radar (SAR) to demonstrate high-resolution wide swath (HRWS) operational modes in spaceborne SAR missions has supported the development of advanced digital beamforming (DBF) techniques. In doing so, one of the challenges to overcome is the temporal variation of the antenna phase centers in the airborne DBF SAR scenario, which significantly degrades the performance of the azimuth reconstruction. Multiple motion compensation (MoCo) solutions have been explored to correct these inconsistencies. However, the compensation of residual phase errors in the Doppler domain remains unresolved when the multi-channel data has an aliased azimuth spectrum. This paper proposes an algorithm that exploits the properties of the DBF azimuth reconstruction to correct these residual motion inconsistencies, although the channels are undersampled. The algorithm modifies the input range-compressed multi-channel data by using an innovative MoCo technique to compensate the phase components coming from undesired 3D time-variant baselines between the different apertures. Furthermore, a 2-step azimuth reconstruction configuration is implemented to account for the polychromatic nature of SAR signals. To test the performance of the algorithm, point target simulations were carried out, in which the impact of a realistic across-track motion, inaccuracies in the digital elevation model (DEM), and variable velocity are analyzed. The results confirm the efficacy of the proposed technique in azimuth ambiguity suppression, where excellent ambiguity suppression is observed after applying the proposed MoCo technique. Finally, the outcome of the simulations is validated with real multichannel data acquired by the German Aerospace Center (DLR) airborne DBFSAR system.