Abstract:

The azimuth superresolution is a technique problem which has been explored continuously in the field of radar. The L₂ norm regularization method is used for the solution to radar azimuth superresolution problem, because of the illcondition encountered in the solution process. The L₁ norm regularization model is also established for the shortage of the L₂ norm regularization method and the sparseness of the target signal. In order to improve the computational efficiency, the L₁ norm regularization model is transformed into a semidefinite programming model which is solved by the predictorcorrector primaldual pathfollowing method. The computer simulation for different signaltonoise ratio (SNR) is made. The preliminary findings show that both methods can be used in radar azimuth super-resolution, and the performance of the L₁ norm regularization method is better under the same conditions， with a strong noise adaptive ability. It shows when SNR is not less than 0 dB, the resolution is increased by 1.7 times.