Satellite Navigation for the Age of Autonomy

Global Navigation Satellite Systems (GNSS) brought navigation to the masses. Coupled with smartphones, the blue dot in the palm of our hands has forever changed the way we interact with the world. Looking forward, cyber-physical systems such as self-driving cars and aerial mobility are pushing the limits of what localization technologies including GNSS can provide. This autonomous revolution requires a solution that supports safety-critical operation, centimeter positioning, and cyber-security for millions of users. To meet these demands, we propose a navigation service from Low Earth Orbiting (LEO) satellites which deliver precision in-part through faster motion, higher power signals for added robustness to interference, constellation autonomous integrity monitoring for integrity, and encryption / authentication for resistance to spoofing attacks. This paradigm is enabled by the 'New Space' movement, where highly capable satellites and components are now built on assembly lines and launch costs have decreased by more than tenfold. Such a ubiquitous positioning service enables a consistent and secure standard where trustworthy information can be validated and shared, extending the electronic horizon from sensor line of sight to an entire city. This enables the situational awareness needed for true safe operation to support autonomy at scale.Comment: 11 pages, 8 figures, 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS

Signal processing techniques for GNSS anti-spoofing algorithms

The Global Navigation Satellite Systems (GNSS) usage is growing at a very high rate, and more applications are relying on GNSS for correct functioning. With the introduction of new GNSSs, like the European Galileo and the Chinese Beidou, in addition to the existing ones, the United States Global Positioning System (GPS) and the Russian GLONASS, the applications, accuracy of the position and usage of the signals are increasing by the day. Given that GNSS signals are received with very low power, they are prone to interference events that may reduce the usage or decrease the accuracy. From these interference, the spoofing attack is the one that has drawn major concerns in the GNSS community. A spoofing attack consist on the transmission of GNSS-like signals, with the goal of taking control of the receiver and make it compute an erroneous position and time solution. In the thesis, we focus on the design and validation of different signal processing techniques, that aim at detection and mitigation of the spoofing attack effects. These are standalone techniques, working at the receiver’s level and providing discrimination of spoofing events without the need of external hardware or communication links. Four different techniques are explored, each of them with its unique sets of advantages and disadvantages, and a unique approach to spoofing detection. For these techniques, a spoofing detection algorithm is designed and implemented, and its capabilities are validated by means of a set of datasets containing spoofing signals. The thesis focuses on two different aspects of the techniques, divided as per detection and mitigation capabilities. Both detection techniques are complementary, their joint use is explored and experimental results are shown that demonstrate the advantages. In addition, each mitigation technique is analyzed separately as they require specialized receiver architecture in order to achieve spoofing detection and mitigation. These techniques are able to decrease the effects of the spoofing attacks, to the point of removing the spoofing signal from the receiver and compute navigation solutions that are not controlled by the spoofer and lead in more accurate end results. The main contributions of this thesis are: the description of a multidimensional ratio metric test for distinction between spoofing and multipath effects; the introduction of a cross-check between automatic gain control measurements and the carrier to noise density ratio, for distinction between spoofing attacks and other interference events; the description of a novel signal processing method for detection and mitigation of spoofing effects, based on the use of linear regression algorithms; and the description of a spoofing detection algorithm based on a feedback tracking architecture

GPS Anomaly Detection And Machine Learning Models For Precise Unmanned Aerial Systems

The rapid development and deployment of 5G/6G networks have brought numerous benefits such as faster speeds, enhanced capacity, improved reliability, lower latency, greater network efficiency, and enablement of new applications. Emerging applications of 5G impacting billions of devices and embedded electronics also pose cyber security vulnerabilities. This thesis focuses on the development of Global Positioning Systems (GPS) Based Anomaly Detection and corresponding algorithms for Unmanned Aerial Systems (UAS). Chapter 1 provides an overview of the thesis background and its objectives. Chapter 2 presents an overview of the 5G architectures, their advantages, and potential cyber threat types. Chapter 3 addresses the issue of GPS dropouts by taking the use case of the Dallas-Fort Worth (DFW) airport. By analyzing data from surveillance drones in the (DFW) area, its message frequency, and statistics on time differences between GPS messages were examined. Chapter 4 focuses on modeling and detecting false data injection (FDI) on GPS. Specifically, three scenarios, including Gaussian noise injection, data duplication, data manipulation are modeled. Further, multiple detection schemes that are Clustering-based and reinforcement learning techniques are deployed and detection accuracy were investigated. Chapter 5 shows the results of Chapters 3 and 4. Overall, this research provides a categorization and possible outlier detection to minimize the GPS interference for UAS enhancing the security and reliability of UAS operations

Radio Frequency Interference Impact Assessment on Global Navigation Satellite Systems

The Institute for the Protection and Security of the Citizen of the EC Joint Research Centre (IPSC-JRC) has been mandated to perform a study on the Radio Frequency (RF) threat against telecommunications and ICT control systems. This study is divided into two parts. The rst part concerns the assessment of high energy radio frequency (HERF) threats, where the focus is on the generation of electromagnetic pulses (EMP), the development of corresponding devices and the possible impact on ICT and power distribution systems. The second part of the study concerns radio frequency interference (RFI) with regard to global navigation satellite systems (GNSS). This document contributes to the second part and contains a detailed literature study disclosing the weaknesses of GNSS systems. Whereas the HERF analysis only concerns intentional interference issues, this study on GNSS also takes into account unintentional interference, enlarging the spectrum of plausible interference scenarios.JRC.DG.G.6-Security technology assessmen

Nanosecond-Level Resilient GNSS-Based Time Synchronization in Telecommunication Networks Through WR-PTP HA

In recent years, the push for accurate and reliable time synchronization has gained momentum in critical infrastructures, especially in telecommunication networks, driven by the demands of 5G new radio and next-generation technologies that rely on submicrosecond timing accuracy for radio access network (RAN) nodes. Traditionally, atomic clocks paired with global navigation satellite systems (GNSS) timing receivers have served as grand master clocks, supported by dedicated network timing protocols. However, this approach struggles to scale with the increasing numbers of RAN intermediate nodes. To address scalability and high-accuracy synchronization, a more cost-effective and capillary solution is needed. Standalone GNSS timing receivers leverage ubiquitous satellite signals to offer stable timing signals but can expose networks to radio-frequency attacks due to the consequent proliferation of GNSS antennas. Our research introduces a solution by combining the white rabbit precise time protocol with a backup timing source logic acting in case of timing disruptive attacks against GNSS for resilient GNSS-based network synchronization. It has been rigorously tested against common jamming, meaconing, and spoofing attacks, consistently maintaining 2 ns relative synchronization accuracy between nodes, all without the need for an atomic clock