Advances in SAR-ISAR blending

Radar signature measurements of targets with or without camouflage in different backgrounds using airborne SAR are complex and expensive. Measurements at many orientations as well as illumination angles have to be performed for each target for completeness. A more efficient solution is to use ground based ISAR measurements of the desired targets and then blend these images into measured SAR scenes. A SAR-ISAR blending method where the target and background are modelled by point scatterer representations is described in this paper. The point scatterer representations for the target and the SAR background are determined by solving two separate inverse problems using ℓ1 and ℓ2-minimization methods. The model for the target measured by ISAR is naturally sparse in the image domain and is therefore solved using an ℓ1-minimization method while the model for the SAR background image that is not sparse is solved using an ℓ2-minimization method. The proposed method is demonstrated and it is determined that it provides an efficient way of evaluating measured ISAR target signatures in measured SAR backgrounds.