A Hybrid Norm Regularization Approach for Radar Forward-looking Angle Super-resolution Imaging

In order to resolve the contradiction between noise suppression and angular resolution improvement of the traditional L
₁
regularization method, this paper proposes a hybrid L
₁
-L
₂
regularization super-resolution method. In the preprocessing stage, the L
₂
norm regularization is utilized to smooth the noise and modify the ill-posed property of the deconvolution process. Then an objective function is established as the L
₁
constraint to increase the angular resolution. Compared with the conventional L
₂
norm regularization method, the resolution is higher; and the sensitivity to noise is reduced compared with the conventional L
₁
norm regularization method. Simulation and experimental data results demonstrate the effectiveness of the hybrid norm regularization method.