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Ground-Moving Target Imaging and Velocity Estimation Based on Mismatched Compression for Bistatic Forward-Looking SAR.

Authors :
Li, Zhongyu
Wu, Junjie
Huang, Yulin
Sun, Zhichao
Yang, Jianyu
Source :
IEEE Transactions on Geoscience & Remote Sensing. Jun2016, Vol. 54 Issue 6, p3277-3291. 15p.
Publication Year :
2016

Abstract

Bistatic forward-looking synthetic aperture radar (BFL-SAR) is a kind of bistatic SAR system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFL-SAR imaging theories and methods have been researched for stationary targets. Unlike the stationary target, the motion of a ground-moving target (GMT) induces unknown range cell migration and additional modulation of the azimuth signal. Thus, to finely image the GMT, one must obtain its velocity parameters accurately, but they are usually unknown. In this paper, a novel GMT imaging and velocity estimation method, which is based on mismatched compression, is proposed for BFL-SAR without a priori knowledge of the GMT's velocity parameters. The main idea behind mismatched compression is to use a presumed azimuth reference function for performing correlated operation with the azimuth signal of the GMT. In general, the Doppler parameters of the presumed azimuth reference function are different from those of the GMT's azimuth signal because the velocity parameters of the GMT are unknown. Therefore, the correlation operation referred to earlier is actually mismatched compression, and the resulting image is shifted and defocused. The shifted and defocused image is utilized to get the real Doppler and velocity parameters of the GMT. The advantage of this method is that not only the GMT can be well focused but also the GMT's velocity can be simultaneously obtained. In addition, this method needs only monochannel antenna. The proposed BFL-SAR GMT imaging and velocity estimation method is validated by numerical simulations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01962892
Volume :
54
Issue :
6
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
115133611
Full Text :
https://doi.org/10.1109/TGRS.2016.2514494