Global navigation satellite systems (GNSS) or satellite navigation is an important technological advancement; however, it is greatly impacted by the effects of space weather, such as ionosphere scintillation. Ionosphere scintillation is one of the causes of errors in the GNSS signals and also has the potential to cause a loss of access to GNSS. Ionosphere scintillation often impacts the polar region; however, the cause is not always known. One potential source of scintillation is polar cap patches. In Ren et al., [2018], a polar cap patch database was created based on the incoherent scatter radar measurements at Resolute Bay (RISR). Using data provided by the CHAIN Network of ionosphere scintillation detected near Resolute Bay in 2016, it can be determined how polar cap patches impact ionosphere scintillation. A statistical analysis as well as event analysis have been performed. Scintillation data from GNSS satellites with an elevation angle over 40 degrees were collected from each patch in the database and were compared to daily average. It was found that statistically there is no obvious phase scintillation or amplitude scintillation increase associated with patch in the polar cap. For the event analysis, three different patch events with and without enhanced scintillation were chosen for in-depth analysis and cross-comparison. Other datasets, including AMPERE FAC and RISR, are used to understand the plasma characteristics and geomagnetic activity conditions during these events.

The Gabor transform can be utilized in an algorithm for compression due to its ability to allow the user to isolate high frequency information to filter. This transform can be implemented using FFT’s to aid in calculating the Gabor coefficients of a particular image. In the C++ programming language, an open source library exists called FFTW that is able to perform FFT’s quickly on the CPU. cuFFT does have a bottleneck during the initial allocation of the input, output, and plan for the desired FFT, but with larger images these became less and less impactful. Image compression algorithms using the Gabor transform can benefit in reduced computational time from cuFFT’s functions.