Super resolution SAR imaging via parametric spectral estimation methods

Super resolution synthetic aperture radar (SAR) image formation via sophist icated parametric spectral estimation algorithms is considered. Parametric spectral estimation methods are devised based on parametric data models and are used to estimate the model parameters. Since SAR images rather than mo del parameters are often used in SAR applications, we use the parameter est imates obtained with the parametric methods to simulate data matrices of la rge dimensions and then use the fast Fourier transform (FFT) methods on the m to generate SAR images with super resolution. Experimental examples using the MSTAR and Environmental Research Institute of Michigan (ERIM) data ill ustrate that robust spectral estimation algorithms can generate SAR images of higher resolution than the conventional FFT methods and enhance the domi nant target features.