Motion Compensation for UAV SAR Based on Raw Radar Data

Unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) is very important for battlefield awareness. For SAR systems mounted on a UAV, the motion errors can be considerably high due to atmospheric turbulence and aircraft properties, such as its small size, which makes motion compensation (MOCO)...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing 2009-08, Vol.47 (8), p.2870-2883
Main Authors:	Mengdao Xing, Mengdao Xing, Xiuwei Jiang, Xiuwei Jiang, Renbiao Wu, Renbiao Wu, Feng Zhou, Feng Zhou, Zheng Bao, Zheng Bao
Format:	Article
Language:	eng
Subjects:	Aircraft Applied geophysics Data mining Doppler effect Doppler radar Earth sciences Earth, ocean, space Error analysis Estimates Exact sciences and technology Inertial navigation Internal geophysics Motion analysis Motion compensation Motion compensation (MOCO) Motion estimation Radar data radar imaging Raw Synthetic aperture radar synthetic aperture radar (SAR) unmanned aerial vehicle (UAV) Unmanned aerial vehicles
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Summary:	Unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) is very important for battlefield awareness. For SAR systems mounted on a UAV, the motion errors can be considerably high due to atmospheric turbulence and aircraft properties, such as its small size, which makes motion compensation (MOCO) in UAV SAR more urgent than other SAR systems. In this paper, based on 3-D motion error analysis, a novel 3-D MOCO method is proposed. The main idea is to extract necessary motion parameters, i.e., forward velocity and displacement in line-of-sight direction, from radar raw data, based on an instantaneous Doppler rate estimate. Experimental results show that the proposed method is suitable for low- or medium-altitude UAV SAR systems equipped with a low-accuracy inertial navigation system.
ISSN:	0196-2892 1558-0644