Jamming And Spoofing mitigation by ProcEssing Receivers of opportunity

Last Updated: 22/02/2023 13:59     Created at: 22/02/2023 13:56

Final Presentation of NAVISP Project EL1 029 now available:

On Friday, February the 17th, 2023, GMV NSL Ltd presented the results of the NAVISP project “Jamming And Spoofing mitigation by ProcEssing Receivers of opportunity (JASPER)”. About 70 people from industry and research institutes followed the interesting presentation and the subsequent interactive Q&A session.

The fast evolution of the Internet of Things (IoT), commercial Cloud platforms, and the future 5G standards, are boosting the development of new applications and technologies in the Position Navigation and Timing (PNT) field. Mobile operating systems provide for example increased access to raw measurements, including GNSS, Wi-Fi and other sensors (as an example, Wi-Fi round-trip time is available in the first developer preview build of Android P), which makes these devices ideal Receivers of Opportunity (RoO) to assist in PNT determination. In this context, the exploitation of GNSS signals, together with other sensors’ measurements and peer-to-peer (P2P) communications, constitute a feasible approach to enable new signal processing techniques. In particular, the collaborative processing of distributed RoO in nearby locations can be used to solve some of the limitations faced by current GNSS receivers in the presence of jamming and spoofing attacks.

The goal of this activity was therefore the development of collaborative positioning techniques using RoOs for the detection and mitigation of jamming and spoofing attacks.  An end-to-end simulator was designed to demonstrate the capabilities of collaborative positioning by utilizing GNSS signals from distributed RoOs and the peer-to-peer (P2P) ranges between them. Machine Learning (ML) models were also applied to exploit the signal characteristics and detect “trusted” RoOs that could be used in collaborative positioning. 

Within the project framework several different models have been implemented: (1) independent solution mode (GNSS-only), (2) independent solution with height-aiding mode, (3) hybrid solution mode (using P2P ranges and sparse GNSS signals), (4) collaborative positioning mode (hybrid solution with ML). Additionally, the simulator included the ability to operate directly in the positioning domain (Direct Positioning Engine, DPE) based on GNSS signals, exploiting a coarse estimation of position and time.

Thanks to the support of NAVISP, a software-based Concept Demonstrator (SW-CD) was developed, implemented, and tested, showing that the collaborative P2P engine implemented can compute the target receiver position by fusing measurements from the available GNSS signals and ranges from nearby trusted RoOs, while the untrusted RoOs, identified based on a ML model, are discarded. More specifically, the ML model was able to detect GNSS spoofing and jamming with an accuracy of about 95%.  It has been observed that the collaborative positioning output from the SW-CD is more robust as a result of detecting and removing untrustworthy RoOs and including additional ranges to the positioning algorithm. However, although the accuracy of the DPE was similar to that of the GNSS receiver, the method was computationally expensive. 

The project was carried out in the scope of NAVISP Element 1, which is dedicated to technology innovation of the European industry in the wide PNT sector.

More detailed information can be found in the slides of the Final Presentation.