Title :
A New Superresolution SAR Imaging Algorithm based on Extrapolation
Author :
Zhang, P. ; Yang, Ruliang
Author_Institution :
Grad. Sch., Chinese Acad. of Sci., Beijing
Abstract :
In this paper, we present an extrapolation approach, which uses minimum weighted norm constraint and minimum variance spectrum estimation, for improving synthetic aperture radar (SAR) resolution. Minimum variance method is a robust high resolution method to estimate spectrum. Based on the theory of SAR imaging, the signal model of SAR imagery is analyzed to be feasible for using data extrapolation methods to improve the resolution of SAR image. The method is used to extrapolate the efficient bandwidth in phase history field and better results are obtained compared with adaptive weighted norm extrapolation (AWNE) method and traditional imaging method using simulated data and actual measured data.
Keywords :
extrapolation; geophysical signal processing; geophysical techniques; radar signal processing; remote sensing by radar; spectral analysis; synthetic aperture radar; SAR imaging theory; SAR signal model; data extrapolation method; efficient bandwidth extrapolation; minimum variance spectrum estimation; minimum weighted norm constraint; superresolution SAR imaging algorithm; synthetic aperture radar; Bandwidth; Extrapolation; Image analysis; Image resolution; Radar polarimetry; Robustness; Signal analysis; Signal resolution; Spectral analysis; Synthetic aperture radar; Extrapolation; Minimum Variance Method; Minimum Weighted Norm; Superresolution; Synthetic Aperture Radar (SAR);
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-2807-6
Electronic_ISBN :
978-1-4244-2808-3
DOI :
10.1109/IGARSS.2008.4779744
