Efficient Implementation of Iterative Adaptive Approach Based on GPU Framework for Radar Super-resolution Imaging

Iterative adaptive approach (IAA) is an effective way to improve the resolution of airborne forward-looking radar imagery. Regretfully, the computational complexity of autocorrelation matrix inversion is too high to reach the real-time technical requirement of radar imaging. In response to this problem, an efficient IAA method based on the graphics processing unit framework (IAA-GPU framework) is proposed in this paper which utilizes the multi-core, parallel, and multi-threaded characteristics of GPU framework to perform IAA processing. Compared with conventional implementation based on CPU framework, the proposed IAA-GPU framework enjoys a preferable computational efficiency without performance degradation. The method of implementing parallel IAA computation based on the GPU framework will be explained in detail, and simulations are given to verify the performance gain.