Study of the GNSS Jamming in Real Environment

GNSS systems are susceptible to radio interferencedespite then operating in a spread spectrum. The commercejammers power up to 2 watts that can block the receiver functionat a distance of up to 15 kilometers in free space.Two original methods for GNSS receiver testing were developed.The first method is based on the usage of a GNSS simulatorfor generation of the satellite signals and a vector signal RFgenerator for generating different types of interference signals.The second software radio method is based on a software GNSSsimulator and a signal processing in Matlab. The receivers weretested for narrowband CW interference, FM modulated signaland chirp jamming signals, and scenarios. The signal to noiseratio usually drops down to 27 dBc-Hz while the jamming tosignal ratio is different for different types of interference. Thechirp signal is very effective.The jammer signal is well propagated in free space while inthe real mobile urban and suburban environment it is usuallystrongly attenuated

PNT cyber resilience : a Lab2Live observer based approach, Report 1 : GNSS resilience and identified vulnerabilities. Technical Report 1

The use of global navigation satellite systems (GNSS) such as GPS and Galileo are vital sources of positioning, navigation and timing (PNT) information for vehicles. This information is of critical importance for connected autonomous vehicles (CAVs) due to their dependence on this information for localisation, route planning and situational awareness. A downside to solely relying on GNSS for PNT is that the signal strength arriving from navigation satellites in space is weak and currently there is no authentication included in the civilian GNSS adopted in the automotive industry. This means that cyber-attacks against the GNSS signal via jamming or spoofing are attractive to adversaries due to the potentially high impact they can achieve. This report reviews the vulnerabilities of GNSS services for CAVs (a summary is shown in Figure 1), as well as detection and mitigating techniques, summarises the opinions on PNT cyber testing sourced from a select group of experts, and finishes with a description of the associated lab-based and real-world feasibility study and proposed research methodology

Advanced Integration of GNSS and External Sensors for Autonomous Mobility Applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Impact Analysis of Standardized GNSS Receiver Testing against Real-World Interferences Detected at Live Monitoring Sites

GNSS-based applications are susceptible to different threats, including radio frequency interference. Ensuring that the new applications can be validated against the latest threats supports the wider adoption and success of GNSS in higher value markets. Therefore, the availability of standardized GNSS receiver testing procedures is central to developing the next generation of receiver technologies. The EU Horizon2020 research project STRIKE3 (Standardization of GNSS Threat reporting and Receiver testing through International Knowledge Exchange, Experimentation and Exploitation) proposed standardized test procedures to validate different categories of receivers against real-world interferences, detected at different monitoring sites. This paper describes the recorded interference signatures, their use in standardized test procedures, and analyzes the result for two categories of receivers, namely mass-market and professional grade. The result analysis in terms of well-defined receiver key performance indicators showed that performance of both receiver categories was degraded by the selected interference threats, although there was considerable difference in degree and nature of their impact

Development of a GPS multi-antenna calibrated platform using COTS components

La vulnerabilitat de les senyals GNSS vers interferències de radiofreqüència i spoofing s'ha convertit en una preocupació en aplicacions de radionavegació que requereixen un alt nivell de precisió i seguretat. Aquesta manca de precisió dels receptors GPS convencionals ha donat pas al desenvolupament de sistemes GPS multi-antena els quals integren diversos front-ends sincronitzats mitjançant un oscil·lador comú. L'objectiu principal d'aquest projecte és el desenvolupament d'una paltaforma GPS de fàcil ús, calibrada i de baix cost utilitzant Software-Defined Radios (SDRs) i antenes GPS comercials. El hardware encarregat d'enregistrar les senyals captades per les diverses antenes GPS està format per tres Universal Software Preipherial Radios i un ordinador personal. La metodologia que es proposa per tal d'aconseguir una sincronització de fase entre els diferents front-ends consisteix en l'ús de les diferències de fase observades d'una senyal de referència per tal de compensar el desfasament existent en les senyals captades per cada USRP. En comptes de fer servir un array d'antenes totalment calibrat i amb una geometria fixa, l'aray que es proposa està format per tres antenes GPS comercials. Aquest enfocament permetrà a l'usuari de canviar la geometria de l'array de tal manera que es podrà adaptar a les necessitats d'aplicació.La vulnerabilidad de las señales GNSS frente a interferencias de radiofrecuencia y spoofing se ha convertido en una preocupación en aplicaciones de radionavegación que requieren un alto nivel de precisión y seguridad. Esta falta de precisión en los receptores GPS convencionales ha dado lugar al desarrollo de sistemas GPS multi-antena los cuales integran distintos front-ends sincronizados utilizando un oscilador común. El objetivo principal de este proyecto es desarrollar una plataforma GPS de fácil uso, calibrada y de bajo coste utilizando Software-Defined Radios (SDRs) y antenas GPS comerciales. El hardware encargado de grabar las señales captadas por las distintas antenas GPS está formado por tres Universal Software Peripheral Radios y un ordenador personal. El método propuesto para conseguir una sincronización de fase entre los distintos front-ends consiste en el uso de las diferencias de fase observadas de una señal de referencia para compensar el desfase existente en las señales captadas por cada USRP. En vez de utilizar un array de antenas totalmente calibrado y con una geomtría fija, el array que se propone está formado por tres antenas GPS comerciales. Este enfoque permitirá al usuario cambiar la geometría del array de modo que se adapte a las necesidades de la aplicación.The vulnerability of GNSS to RF interference and spoofing has become more and more a concern for navigation applications requiring a high level of accuracy and reliability. This lack of accuracy of the GPS conventional receivers has triggered the development GPS multi-antenna systems, which integrate three or more GPS front-ends referenced to a common oscillator. The main purpose of this project is to develop a low cost and ease of deployment GPS calibrated multi-antenna platform by using both Commercial-Off-The Shelf (COTS) software-defined radios (SDRs) and GPS antennas. The signal collection hardware built to collect array data sets for each antenna consists of three Universal Software Radio Peripheral (USRP) and one Personal Computer (PC). The method proposed to achieve phase synchronization between the different front-ends consists of using a phase difference of arrival mechanism based on a synthetic GPS signal reference transmitter. The antenna array proposed is composed by three COTS GPS antennas instead of using a custom designed and fully calibrated antenna array. This approach allows the user to change the desired layout depending on the application field

Unconditionally Secure Authentication and Integrity Protection for the Galileo Open Service Signal

The operational GNSSs do not offer authentication and integrity protection for the Open Service (OS) signal/message. But it is urgently needed, since several attacks can threat the OS user. By this reason the Galileo GNSS is working on this issue. This thesis contributes at the problem by adopting an approach as generic as possible, which outlines a theoretical bound on the key size. Therefore, the focus is providing data and signal unconditionally secure authentication and integrity pro

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors

Signal classification at discrete frequencies using machine learning

Incidents such as the 2018 shut down of Gatwick Airport due to a small Unmanned Aerial System (UAS) airfield incursion, have shown that we don’t have routine and consistent detection and classification methods in place to recognise unwanted signals in an airspace. Today, incidents of this nature are taking place around the world regularly. The first stage in mitigating a threat is to know whether a threat is present. This thesis focuses on the detection and classification of Global Navigation Satellite Systems (GNSS) jamming radio frequency (RF) signal types and small commercially available UAS RF signals using machine learning for early warning systems. RF signals can be computationally heavy and sometimes sensitive to collect. With neural networks requiring a lot of information to train from scratch, the thesis explores the use of transfer learning from the object detection field to lessen this burden by using graphical representations of the signal in the frequency and time domain. The thesis shows that utilising the benefits of transfer learning with both supervised and unsupervised learning and graphical signal representations, can provide high accuracy detection and classification, down to the fidelity of whether a small UAS is flying or stationary. By treating the classification of RF signals as an image classification problem, this thesis has shown that transfer learning through CNN feature extraction reduces the need for large datasets while still providing high accuracy results. CNN feature extraction and transfer learning was also shown to improve accuracy as a precursor to unsupervised learning but at a cost of time, while raw images provided a good overall solution for timely clustering. Lastly the thesis has shown that the implementation of machine learning models using a raspberry pi and software defined radio (SDR) provides a viable option for low cost early warning systems