Efficient and accurate approximation of superresolution spectral estimation methods for SAR imaging

Superresolution methods of spectral estimation have shown much promise for creating high quality SAR images that are devoid of the inherent shortcomings of classical Fourier techniques. However, many modern spectral estimation techniques involve the estimation of a correlation matrix and manipulations thereof, both of which can be prohibitively expensive. While efficient methods of computing these spectral estimation techniques have been explored in the literature, for large scenes with high resolution, it is often still too expensive to compute and store the data necessary for the computations. These techniques thus have had limited application in the vast array of SAR imaging problems. This paper presents several methods for generating accurate approximations of these spectral estimation techniques while further improving the computational efficiency and reducing the storage burden.