Detecting jamming in OSNET using machine learning

Disclosed is an automatic interference/jamming detection system for use with a Global Navigation Satellite System (GNSS) receiver or a GNSS receiver and off-the-shelf jamming detector. The automatic jamming detection system utilizes one of the following two techniques: using a jamming detector in conjunction with a GNSS receiver in order to analyse received data for key data indicators for suspicious interference/jamming activities such as signal-to noise ratio, phase or maximum power, or using a trained jamming detection algorithm to convert received/stored GNSS data into spectrograms to visually highlight anomalies or potential interference/jamming events and then further using a Box-Cox transform to train the algorithm in order to transform data into a normal distribution for comparison against user tuneable thresholds to further highlight potential interference/jamming events.