Abstract | ||
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This paper concerns the compensation of track deviations in high-resolution automobile synthetic aperture radar (SAR). We establish the geometry in which the automobile SAR raw data is acquired. Based on the derived model, the research investigates the impact of track deviations on the final focused image quality and we propose motion compensation (MOCO) strategy which can be applied to obtain a well-focused SAR image. This paper presents how to obtain the accurate positions of the antenna phase center (APC) using the velocity and attitude angles measured by inertial navigation system (INS)/global positioning system (GPS), and proposes a new method to compensate the forward velocity errors which are decomposed into two components and compensated individually, that is, high-order and low order phase compensation. Finally, the results from real data are presented to validate the whole analysis and the proposed procedure. |
Year | DOI | Venue |
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2014 | 10.1080/01431161.2014.930203 | International Journal of Remote Sensing |
Keywords | Field | DocType |
synthetic aperture radar,motion compensation,image quality,high-resolution automobile synthetic aperture radar,apc,track deviation compensation,radar antennas,gps,high-order phase compensation,moco strategy,low order phase compensation,attitude angle measurement,inertial navigation system,global positioning system,velocity angle measurement,ins,forward velocity error compensation,data acquisition,sar imaging,automobile synthetic aperture radar,motion compensation strategy,radar resolution,antenna phase center,radar imaging,inertial navigation,geometry,navigation,azimuth,tracking,radar tracking,chirp | Radar engineering details,Continuous-wave radar,Radar,Computer vision,Radar imaging,Computer science,Synthetic aperture radar,Motion compensation,Inverse synthetic aperture radar,Artificial intelligence,3D radar | Conference |
Volume | Issue | ISSN |
35 | 13 | 0143-1161 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
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Ahmed Azouz | 1 | 0 | 0.68 |
Zhenfang Li | 2 | 103 | 11.78 |