Formation of HRR profiles by nonquadratic optimization for improved feature extraction

We propose a new method for superresolution, feature-enhanced reconstruction of high range-resolution (HRR) radar profiles. We pose the problem of the formation of the HRR profiles from phase history data as an optimization problem. Resolution and feature enhancements are achieved by imposing non-quadratic regularizing constraints on the solution of the optimization problem. We present experimental results on synthetic and measured data, and compare the proposed method to currently available techniques. This analysis shows the ability of the proposed method to preserve high-resolution features such as the locations and amplitudes of the dominant scatterers in the HRR profile. This suggests that the technique may potentially help improve the performance of HRR target recognition systems.

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