GNSS Interference Classification Using Handcrafted Signal Features and Lightweight Neural Models
This paper compares three approaches to six-class Global Navigation Satellite System (GNSS) interference classification: classical classifiers trained on 17 handcrafted spectral and statistical features, a one-dimensional convolutional neural network using two-channel raw IQ samples, and a two-dimensional convolutional...