LAUSR

Geosynchronous-Earth-orbit (GEO) synthetic aperture radar (SAR) provides excellent continuous observing capability and large swath. However, the extremely long synthetic aperture time, the curved orbit, and the nonplanar ground surface cause serious spatial variance in the GEO SAR signal. In this article, a novel fast Cartesian back-projection (BP) algorithm based on subaperture imaging on ground and multistage fusion is proposed for accurately and efficiently imaging of GEO SAR. The imaging grids are arranged on the ground surface to avoid the azimuth defocusing caused by the flat ground approximation. Then, a new two-step spectrum compression method is derived to solve the spectrum aliasing of subaperture images. Also, a multistage image fusion method is adopted to combine all the subaperture images with high efficiency. The computational complexity and the approximation of the proposed algorithm are also discussed. Simulation results verify the effectiveness of the proposed algorithm.