Modelling the Noise of GNSS Signals under Jamming Conditions

Abstract

Global Navigation Satellite Systems (GNSS) are increasingly used as the main source for Positioning, Navigation and Timing (PNT) information for maritime and inland water applications. With the rising availability of cheap jamming devices such as Personal Privacy Devices (PPD), there is real threat to GNSS based navigation. Therefore, it becomes of upmost importance to estimate the accuracy of the satellite signals, even under disturbance. The presented work examines the influence of jamming on the noise of the signals and if it can be modeled. Laboratory experiments showed that it is possible to accurately estimate the noise in jamming conditions which is even consistent with undisturbed measurements. Hence, the derived model describes the noise of GNSS signals in scenarios with and without jamming. It uses the elevation angles of the satellites and the Signal-toNoise Ratio (SNR) of its signals to estimate the respective noise. The parameters of the model are calculated by fitting them to real measurement data of scenarios with different amount of jamming. The initial results show that this model estimates the noise of the signals better than classic weighting schemes using only the elevation angles or just the SNR. This shows the potential of the model to be used in multisensor fusion scheme as a weighting scheme in an iterative least squares position solver or as a variance estimator in a Kalman filter in demanding environments.