A GPU implementation of the inverse fast multipole method for multi-bistatic imaging applications

This paper presents a parallel implementation of the Inverse Fast Multipole Method (IFMM) for multi-bistatic imaging configurations. NVIDIA's Compute Unified Device Architecture (CUDA) is used to parallelize and accelerate the imaging algorithm in a Graphics Processing Unit (GPU). The algorithm is validated with experimental data, collected by a Frequency-Modulated Continuous Wave (FMCW) radar system operating in the 70-77 GHz frequency band. The proposed GPU-based IFMM algorithm accelerated the single-core CPU version by a factor of 46.

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