Acceleration of fast factorized back projection algorithm for bistatic SAR

In this paper, we present an accelerated fast factorized back-projection algorithm designed for bistatic SAR data. This method supports a precise bistatic SAR image reconstruction and can attain high execution efficiency. Key to this method is the optimized parallel implementation of the original algorithm that can be executed on GPU. We make effort to a parallelization of factorized back-projection by a reasonable parallel strategy so that it can be implemented by CUDA on GPU. Moreover, we also do some optimization for a further improvement, including memory optimization and phase compute optimization, and when it comes to the translational-invariant data, an extra slant range compute optimization have been done yet. The validity and advantage of proposed approach are verified by simulated X-band bistatic SAR data and experimental data.