Sparse modeling for polarimetric radar

In this paper, we develop a sparse model to represent the data recorded by a polarimetric, coherent radar. We produce this model defining an over-complete library of possible target responses in the range-polarization space. Then, we employ compressive sensing methods to infer the position and the scattering matrix of the target. Using real radar data, we show that this new approach offers better interference rejection over other methods.