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A two-dimensional (2D) sparse signal model is developed for pulse Doppler MIMO radars. Using this model, we develop the 2D sparse learning via iterative minimization (2D SLIM) algorithm. Simulation results show that the 2D SLIM compared to the 1D SLIM drastically reduces the computational burden while both of them have the same performance. Also, for estimation of range-angle-Doppler parameters, the 2D SLIM outperforms the matched filter (MF), smoothed L0-norm (SL0), iterative adaptive approach (IAA), and spectral projected gradient for l 1-norm minimization (SPGL1) algorithms.

Two-dimensional SLIM with application to pulse Doppler MIMO radars