15 April 2008 Autofocus for 3D imaging
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Abstract
Three dimensional (3D) autofocus remains a significant challenge for the development of practical 3D multipass radar imaging. The current 2D radar autofocus methods are not readily extendable across sensor passes. We propose a general framework that allows a class of data adaptive solutions for 3D auto-focus across passes with minimal constraints on the scene contents. The key enabling assumption is that portions of the scene are sparse in elevation which reduces the number of free variables and results in a system that is simultaneously solved for scatterer heights and autofocus parameters. The proposed method extends 2-pass interferometric synthetic aperture radar (IFSAR) methods to an arbitrary number of passes allowing the consideration of scattering from multiple height locations. A specific case from the proposed autofocus framework is solved and demonstrates autofocus and coherent multipass 3D estimation across the 8 passes of the "Gotcha Volumetric SAR Data Set" X-Band radar data.
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Forest Lee-Elkin, "Autofocus for 3D imaging", Proc. SPIE 6970, Algorithms for Synthetic Aperture Radar Imagery XV, 69700O (15 April 2008); doi: 10.1117/12.790433; https://doi.org/10.1117/12.790433
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