Two-Dimensional Super-Resolution Imaging of Radar Target Based on Fourth-Order Mixed Cumulants
基于四阶混合累积量的雷达目标二维超分辨成像

A new method for two-dimensional super-resolution imaging of radar target in colored Gaussian noise, called two-dimensional FOMC (Fourth-Order Mixed Cumulants) based ESPRIT (2d-FOMCESPRIT), is presented in this paper. The image is improved for the FOMC could eliminate the Gaussian noise automatically. Additionally this method is computationally much less intensive by holding the dimensions of the feature matrix in the presence of long records. Simulation results show that this method has better image quality than other methods.