NDLI: Wavenumber domain focusing of squinted SAR data with a curved orbit geometry

Content Provider	IEEE Xplore Digital Library
Author	Michel, T. Hensley, S.
Copyright Year	2008
Description	Author affiliation: Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA (Michel, T.; Hensley, S.)
Abstract	Synthetic Aperture Radar systems provide raw data that need focusing to achieve full-resolution imaging. Current SAR applications, including interferometry, require accurate, phase-preserving, and precisely co-registered coherent images over large ground swaths with the highest achievable resolution. In addition to these challenges, stripmap SAR data may be acquired with an off-broadside (squinted) geometry, either by design or through platform motion. The precise batch focusing of these large aperture and wide bandwidth data sets is known to require a 2D frequency processing approach. The standard wave domain focusing algorithm, however, is only exact for data acquired on a rectilinear trajectory. We investigate a generalization of the standard omega-k focusing formulation that allows curved data acquisition tracks. The new formulation can be used in conjunction with a known extension for conical, squinted imaging grids. The approximations necessary to allow the generalized geometry are analysed to determines the range of applicability of the proposed algorithm. The theory is validated using data simulated with parameters similar to the UAVSAR L-band SAR system.
Starting Page	492
Ending Page	496
File Size	288285
Page Count	5
File Format	PDF
ISBN	9781424429400
ISSN	10586393
DOI	10.1109/ACSSC.2008.5074454
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geometry Focusing Synthetic aperture radar High-resolution imaging Interferometry Image resolution Bandwidth Frequency Data acquisition Radar tracking
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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