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Sensors 2016, 16(7), 1091; doi:10.3390/s16071091

Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

1
School of Electronics and Information Engineering, Beihang University, Beijing 100191, China
2
Beijing Institute of Remote Sensing Information, Beijing 100192, China
*
Author to whom correspondence should be addressed.
Academic Editor: Assefa M. Melesse
Received: 17 May 2016 / Revised: 1 July 2016 / Accepted: 8 July 2016 / Published: 14 July 2016
View Full-Text   |   Download PDF [6095 KB, uploaded 14 July 2016]   |  

Abstract

Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. View Full-Text
Keywords: geosynchronous synthetic aperture radar; imaging; spatial variance correction; time-frequency scaling geosynchronous synthetic aperture radar; imaging; spatial variance correction; time-frequency scaling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yu, Z.; Lin, P.; Xiao, P.; Kang, L.; Li, C. Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling. Sensors 2016, 16, 1091.

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