This paper presents a random-forest-based machine-learning algorithm to automatically
detect satellite oscillator anomalies using dual-or triple-frequency GPS carrier-phase …

This paper presents a random forest-based machine learning algorithm to automatically
detect satellite oscillator anomalies using dual-or triple-frequency GPS carrier phase …

In this paper, we propose a machine-learning-based approach to automatically detect a
satellite oscillator anomaly. A major challenge is to differentiate an oscillator anomaly from …

This paper applies a machine learning-based satellite oscillator anomaly detection method
to high rate GNSS receiver carrier phase data collected by the University of Colorado …

In this paper, we propose a machine learning-based approach to automatically detect
satellite oscillator anomaly. A major challenge is to differentiate an oscillator anomaly from …

A new system for the detection and continuous monitoring of GPS signal anomalies is
presented. The anomaly detection system is based on the High Rate Tracking Receiver …

In this paper, we propose a machine learning-based approach to automatically detect
satellite oscillator anomaly using dual frequency signals. One major challenge is that both …

This paper presents a radial basis function (RBF) support vector machine (SVM)-based
machine learning (ML) algorithm to automatically detect Galileo satellite oscillator anomalies …

GPS carrier phase measurements are widely used in high accuracy navigation and timing
applications. However, anomalies can exist in these measurements, which if not accounted …

" GPS spectrum is increasingly affected by the ever increasing sources of unintentional and
possibly intentional interference. Continuous realtime monitoring of GPS for detection and …