Detection of GNSS ionospheric scintillations based on machine learning decision tree

Abstract

This paper proposes a methodology for automatic, accurate, and early detection of amplitude ionospheric scintillation events, based on machine learning algorithms, applied on big sets of 50 Hz postcorrelation data provided by a global navigation satellite system receiver. Experimental results on real data show that this approach can considerably improve traditional methods, reaching a detection accuracy of 98%, very close to human-driven manual classification. Moreover, the detection responsiveness is enhanced, enabling early scintillation alerts.