  This paper presents a method for imaging of moving targets using multi-static
SAR by treating the problem as one of spatial reflectivity signal inversion
over an overcomplete dictionary of target velocities. Since SAR sensor returns
can be related to the spatial frequency domain projections of the scattering
field, we exploit insights from compressed sensing theory to show that moving
targets can be effectively imaged with transmitters and receivers randomly
dispersed in a multi-static geometry within a narrow forward cone around the
scene of interest. Existing approaches to dealing with moving targets in SAR
solve a coupled non-linear problem of target scattering and motion estimation
typically through matched filtering. In contrast, by using an overcomplete
dictionary approach we effectively linearize the forward model and solve the
moving target problem as a larger, unified regularized inversion problem
subject to sparsity constraints.
