Nowadays, software-defined Bags - Emesis Bags radio (SDR) has become a common approach to evaluate new algorithms.However, in the field of Global Navigation Satellite System (GNSS) adaptive array anti-jamming, previous work has been limited due to the high computational power demanded by adaptive algorithms, and often lack flexibility and configurability.In this paper, the design and implementation of an SDR-based real-time testbed for GNSS adaptive array anti-jamming accelerated by a Graphics Processing Unit (GPU) are documented.This testbed highlights itself as a feature-rich and extendible platform with great flexibility and configurability, as well as high computational performance.Both Space-Time Adaptive Processing (STAP) and Space-Frequency Adaptive Processing (SFAP) are implemented with a wide range of parameters.
Raw data from as many as eight antenna elements can be processed in real-time in either an adaptive nulling or beamforming mode.To fully take advantage of the parallelism resource provided by Raspberry Ketones the GPU, a batched method in programming is proposed.Tests and experiments are conducted to evaluate both the computational and anti-jamming performance.This platform can be used for research and prototyping, as well as a real product in certain applications.