  We propose a new compressive imaging method for reconstructing 2D or 3D
objects from their scattered wave-field measurements. Our method relies on a
novel, nonlinear measurement model that can account for the multiple scattering
phenomenon, which makes the method preferable in applications where linear
measurement models are inaccurate. We construct the measurement model by
expanding the scattered wave-field with an accelerated-gradient method, which
is guaranteed to converge and is suitable for large-scale problems. We provide
explicit formulas for computing the gradient of our measurement model with
respect to the unknown image, which enables image formation with a sparsity-
driven numerical optimization algorithm. We validate the method both
analytically and with numerical simulations.
