Compressive sensing for synthetic aperture imaging using a sparse basis transform

We consider the problem of active high-resolution imaging using synthetic aperture techniques, such as synthetic aperture radar (SAR) or synthetic aperture sonar (SAS). In order to reduce storage, processing power and energy requirements a compressive sensing framework is adopted that allows to reduce the number of measurements while maintaining range resolution and image quality. We consider the approach from Alonso et al. where compressive sensing is considered as an alternative to matched filtering for range focusing while keeping along-track focusing for imaging unmodified. This approach is extended by a sparse basis transform for range profiles that allows for deviations from the implicit point target model assumption. A synthetic aperture ultrasound imaging system is build that implements the presented techniques in a laboratory setup. Range profiles and images of this setup are considered to evaluate the system performance in terms of resolution and image quality.