This paper presents a method for imaging of moving targets using multi-static radar by treating the problem as one of joint spatial reflectivity signal inversion with respect to an overcomplete dictionary of target velocities. Existing approaches to dealing with moving targets in SAR solve the nonlinear problem of target scattering and motion estimation typically through decoupled 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. This unified framework allows estimation of scatter motion and reflectivity to be done in an optimal and global way. We show examples of the potential of the new method for sensing configurations with transmitters and receivers randomly dispersed in a multi-static geometry within a narrow forward cone around the scene of interest.
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Stojanovic et al. (2010) studied this question.
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