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Processing of Spaceborne Squinted Sliding Spotlight and HRWS TOPS Mode Data Using 2-D Baseband Azimuth Scaling.

Authors :
He, Feng
Dong, Zhen
Zhang, Yongsheng
Jin, Guanghu
Yu, Anxi
Source :
IEEE Transactions on Geoscience & Remote Sensing. Feb2020, Vol. 58 Issue 2, p938-955. 18p.
Publication Year :
2020

Abstract

This article presents an efficient 2-D baseband azimuth scaling (2-D BAS) approach for the focusing of data acquired in the spaceborne squinted sliding spotlight and high-resolution wide-swath (HRWS) terrain observation by progressive scan (TOPS) imaging modes. The existing approaches can become inefficient or invalid due to the coexistence of central “absolute” and marginal “relative” squint in the above-mentioned modes. In this article, the signal properties of spaceborne squint synthetic aperture radar (SAR) with the antenna electronically steering in the azimuth dimension are analyzed first, based on which a new parity-decomposition-based range equation (PDRE) is presented to dedicatedly model the range histories of targets illuminated by the rotating beam. A novel 2-D BAS approach is then developed to remove the odd asymmetric part but preserve the even symmetric part of PDRE, which means a “true derotation” for eliminating the effect of both absolute and relative squints caused by the beam rotation. An even-order-multinomial perturbation function is applied and integrated into a range-Doppler-based SAR processing kernel to efficiently compensate the azimuth variation of high-order range cell migration (RCM) and azimuth phase modulation caused by the 2-D BAS. The proposed processor is efficient, since none of the data extension, the postprocessing for resolving focused-domain folding, or the 2-D frequency-domain interpolation at high squint is needed. Simulations with point targets in the squinted sliding spotlight and HRWS TOPS modes are used to validate the developed algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01962892
Volume :
58
Issue :
2
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
143312982
Full Text :
https://doi.org/10.1109/TGRS.2019.2941983