Paper Info
Title
Geometric Self-Calibration of YaoGan-13 Images Using Multiple Overlapping Images.
Abstract
Geometric calibration is an important means of improving the absolute positioning accuracy of space-borne synthetic aperture radar imagery. The conventional calibration method is based on a calibration field, which is simple and convenient, but requires a great deal of manpower and material resources to obtain ground control points. Although newer cross-calibration methods do not require ground control points, calibration accuracy still depends on a periodically updated reference image. Accordingly, this study proposes a geometric self-calibration method based on the positioning consistency constraint of conjugate image points to provide rapid and accurate calibration of the YaoGan-13 satellite. The proposed method can accurately calibrate geometric parameters without requiring ground control points or high-precision reference images. To verify the absolute positioning accuracy obtained using the proposed self-calibration method, YaoGan-13 Stripmap images of multiple regions were collected and evaluated. The results indicate that high-accuracy absolute positioning can be achieved with a plane accuracy of 3.83 m or better for Stripmap data, without regarding elevation error. Compared to the conventional calibration method using high-accuracy control data, the difference between the two methods is only about 2.53 m, less than the 3-m resolution of the image, verifying the effectiveness of the proposed self-calibration method.
Year
DOI
Venue
2019
10.3390/s19102367
SENSORS
Keywords
Field
DocType
YaoGan-13,geometric accuracy,self-calibration
Synthetic aperture radar imagery,Computer vision,Satellite,Reference image,Electronic engineering,Artificial intelligence,Elevation,Engineering,Calibration
Journal
Volume
Issue
ISSN
19
10
1424-8220
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Guo Zhang14911.45
Mingjun Deng2214.63
Chenglin Cai301.01
Ruishan Zhao4213.28