| Summary: | Due to geosynchronous synthetic aperture radar’s (GEO SAR) high orbit and low relative speed, the integration time reaches up to hundreds of seconds for a fine resolution. The short revisit cycle is essential for remote sensing applications such as disaster monitoring and vegetation measurements. Three-dimensional (3D) scene imaging mode is crucial for long-term observation using GEO SAR. However, this mode will bring a new kind of space-variant error in elevation. In this paper, we focus on the analysis of the elevation space-variant error. First, the decorrelation problems caused by the spatial variation are presented. Second, by combining with the SAR imaging geometry, the elevation spatial variation is decomposed into two-dimensional (2D) space variation of range and azimuth. Third, an imaging algorithm is proposed to solve the 3D space variation and improve the focusing depth. Finally, simulations with dot-matrix targets and distributed targets are performed to validate the imaging method.
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