Range-azimuth joint ISAR super-resolution imaging method based on frequency-stepped signal

For the sparse frequency-stepped (SFS) radar signal which is sparse both in range and azimuth, a novel range-azimuth joint ISAR Imaging method is proposed based on compressive sensing (CS) theory. Firstly, the echo model of the SFSS is established. Secondly, the range-azimuth joint sparse base is built, which is sparse both in the range and azimuth dimension. Finally, the super-resolution ISAR Imaging can be realized via the 2D-Smoothed L0 algorithm which can dispose this echo model in matrix domain directly. Some performances of the proposed algorithm such as complexity and the super resolution capability are also analyzed and some corresponding results are given. At last, theoretical analysis and simulation experiments verify that the proposed algorithm have a better imaging performance and a faster processing speed at different sparse conditions and sparse patterns.