The paper presents a relaxation-basedautofocus (AUTORELAX) algorithm that can be used to compensate for the aperture errors in curvilinear synthetic aperture radar (CLSAR) and to extract three-dimensional target feat...
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The paper presents a relaxation-basedautofocus (AUTORELAX) algorithm that can be used to compensate for the aperture errors in curvilinear synthetic aperture radar (CLSAR) and to extract three-dimensional target features. A self-contained detailed derivation of the data model for the autofocus problem in CLSAR is presented. Experimental and simulation results show that AUTORELAX can be used to significantly improve the estimation accuracy of the target parameters.
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