Computing of bistatic cross-ambiguity function on GPU

The real-time computation of cross ambiguity function (CAF) using brute force and block processing methods is a challenging task for parallel programming techniques. CAF is a key function for successful location tracking by passive radar systems. In this paper, the comparison of CAF methods computation and using a Graphics Processing Unit (GPU) are presented. The main goal of the research is to compare the computation efficiency and speed of the CAF methods on the GPU hardware with a single or multi-Core PC workstation. The results show the highest speed-up factor using GPU for all CAF methods.