A Contrast Optimization Algorithm for Back-Projection Image Reconstruction in Noncooperative ISAR Imaging

We consider very high-resolution inverse synthetic aperture radar (ISAR) imaging of noncooperative objects exhibiting challenging unknown motions using the time domain back-projection algorithm for image reconstruction. We propose a contrast optimization approach for the data-driven motion compensation problem, in which a novel approach using the derivatives of the loss function is utilized in the optimization. The translation and the rotation of the object are estimated simultaneously using first order numerical optimization. In numerical experiments, the proposed optimization approach was able to estimate highly nonlinear translational and rotational motions producing well-focused ISAR images.