Radio Frequency Interference is a recognized and by some measures growing problem in the GNSS user community. Since 2019 SINTEF has operated a distributed RFI monitoring network of Advanced RFI Detection Analysis and Alerting System (ARFIDAAS) units which collect and characterize RFI events over the entirety of the L-band used by GNSS navigation signals. RFI events detected by the network are characterized, and the raw data captured and sent to centralized cloud storage which allows for flexible and repeated analysis of the entire database of detected events, including the ability to identify novel and evolving jamming signal types. Having captured more than fifty thousand events, our efforts have turned to attempting to follow the apparent evolution of the malicious signal structures over the past years, investigating the structure of new observed jamming signals, as well as developing automated test options based on the captured live data for receiver performance evaluation.
Since 2021 SINTEF has noticed the detection and in some cases proliferation of 'modernized' jamming signals which appear specially crafted to cause additional or increased impacts on GNSS receivers relative to the traditional RFI signatures. The new modulation types appear to have characteristics which are specifically designed to defeat families of mitigations that were being integrated into GNSS receivers over recent years. As at least one of these new signal types has been detected both by a roadside ARFIDAAS monitoring station as well as from the air by external monitoring of state actor transmissions, it is an unfortunate supposition that the motivation for the evolution of the RFI signals is to further degrade specific models of GNSS receiver in extensive use.
To keep up with the rapidly evolving GNSS RFI threat space a Hardware In The Loop (HITL) simulation framework has been developed which allows the controlled and repeatable exposure of multiple makes and models of GNSS receivers to jamming signal types over not just power level variations but also over repetition rate, swept bandwidth and other variables to stimulate and evaluate response sensitivities to entire modulation families not just individual signal realizations. One of the novel elements of this approach is the evaluation of receiver sensitivity to the entirety of the parameter space observed by ARFIDAAS as well as signals which include multiple simultaneous time modulated components.
The proposed article will discuss the application of the extensive database of live captured ARFIDAAS source data to inform the threat space simulation, present new RFI jamming signal types observed by the monitoring network, review the design of the automated simulation framework system, and provide a summary of the results produced by a number of common GNSS receiver engines when subjected to these signals. Particular attention will be given to the specific impact cases of concern whereby the new and evolved jamming signals show up to five times more observable degradation in terms of carrier phase noise to some receivers relative to others. Results indicate that some receiver implementations are particularly vulnerable to some of the novel RFI modulation types recently detected.

In the field of GNSS the combination of multiple sensors is a widely used procedure to improve the reliability and robustness of a navigation system. A GNSS/INS sensor fusion is usually used in many applications. In this paper the focus lies on the combination of multiple GNSS receivers to a multi-receiver system. Therefore, a Multi-receiver vector tracking (MRVT) algorithm is used to improve the reliability and robustness of the receiver system. A MRVT algorithm realizes a collaborative processing of multiple I&Q samples from multiple receivers in a receiver network. Within this advanced tracking technique, a single extended Kalman Filter processes the raw GNSS signals. This kind of receiver combination can be used in kinematic (e.g. trajectory and attitude determination, …) as well as static (e.g. GNSS reference/monitoring network, …) applications. In the authors previous publications* the implemented algorithm is already described and analysed in different ways. This publication provides a deeper analysis into the robustness of the developed MRVT algorithm under different interference (i.e. jamming situations). The impact of different jammer types: Amplitude Modulation (AM), Frequency Modulation (FM), Swept Continuous Wave (SCW) and White Gaussian Noise (WGN) is investigated and the performance of the MRVT algorithm is presented in the paper. Therefore, different scenarios are simulated with a signal simulator. The results show that the robustness can be significantly improved in situations where at least one receiver is unaffected by jamming. This paper also analyses the performance of the algorithm in the case of all receivers being affected by interference.

GPS/GNSS is a key technology in all areas of navigation and timing, enabling a a great variety of applications autonomous driving, precise agriculture, LEO satellite positioning and many more. As the GPS/GNSS signals are very weak, they are easy to inferfere with. In addition, they can be spoofed with false signals. Jamming and spoofing attacks have increased over time, especially in the context of recent military conflicts. Most receivers are not protected against jamming and spoofing attacks. But for many applications, especially safety of life ones, it is crucial to ensure secure operation, good accuracy and a high integrity.

A crucial part of achieving this security and integrity is repeatable, controlled and extensive testing. The most efficient test method is dedicated and sophisticated GNSS test equipment: e.g. GPS/GNSS RF simulators with embedded Jamming and Spoofing signal generation.

Here we would like to present an overview of different test methods and present tools and and new, enhanced functionality for jamming and spoofing RF signal simulation, with and without synchronization to live sky signals. Enhancements include:
• new jamming waveforms and a high continuous dynamic power range of the jamming signals
• multiple spoofing vehicles and transmitters
• multi-copy constellations for spoofing
• emulation of the influence of 3D-terrain on spoofing and jamming signals from ground-based transmitters