Research Program Security

GPS is essential not only for navigation, but also for the precise timing needed by telecommunications, financial networks, power grids, autonomous systems, and other critical infrastructure. However, GPS signals are extremely weak when they reach the ground and can therefore be easily disrupted by intentional jamming or other sources of interference. Existing protection methods often rely on complex signal processing or large, expensive antenna arrays, limiting their use in compact and cost-sensitive systems. This project will develop a new generation of compact GPS antennas with built-in protection against interference. It combines two complementary approaches. The first uses specially engineered metamaterial structures around the antenna to passively suppress unwanted signals before they enter the receiver. The second uses a reconfigurable antenna that can adapt its radiation pattern and create a “blind spot” in the direction of an interference source. The antennas will be designed, fabricated, and experimentally tested under realistic GPS interference conditions. The project aims to provide a compact, low-cost, and energy-efficient alternative to conventional anti-jamming systems, improving the resilience of future navigation and timing technologies for both civilian and security applications.

A gyroscope is a device that measures rotation by maintaining a fixed orientation in space, largely independent of the motion of its surroundings. Gyroscopes are essential components of inertial navigation systems and are widely used in satellites, aircraft, drones, and autonomous vehicles. Their sensitivity directly determines the precision and reliability of navigation.

The goal of this project is to develop a mechanical gyroscope based on an optically levitated nanoparticle spinning about its symmetry axis in ultrahigh vacuum. To achieve unprecedented sensitivity, we will explore ultrahigh rotation frequencies in the gigahertz regime together with quantum-limited readout. We will develop a multi-stage sensing protocol to detect and quantify rotations and systematically evaluate the gyroscope’s ultimate sensitivity, stability, and operational performance.

Chip-scale atomic clocks can provide a highly stable time and frequency reference with better long-term accuracy than other miniaturized technologies such as crystal oscillators. Because every atom of a given element behaves identically, atomic clocks are an ideal natural reference. Using light rather than microwaves to read out this reference can further boost the stability by a factor of 1000 or more. The required optical (or photonic) circuits, which are analogous to electronic circuits but use laser light instead of electrical signals, are being developed in academic research groups and companies across Switzerland. These include chip-scale stabilized lasers and frequency combs (devices that link optical and microwave signals), as well as integrated modulators and detectors interfaced with a microscopic vapor cell. The team behind this project has expertise in both optical clock technologies and photonic circuits, and it aims to establish a supply chain for integrated optical clocks within Switzerland. This will require partnering with the most relevant academic and commercial players. Along this path, we will experimentally characterize key laser components in our laboratory and evaluate the feasibility of developing an autonomous Swiss optical clock for position, navigation, and timing applications, independent of satellite navigation systems (GNSS).

Global Navigation Satellite Systems (GNSS) are crucial for modern positioning, navigation, and timing, but their low-power signals are increasingly vulnerable to jamming and spoofing. Conventional defense systems rely on rigid, binary detection that often shuts down GNSS operations entirely when interference is flagged, disrupting critical services. Such disruptions can paralyze air traffic, halt transportation logistics, and cause cascading failures across power grids, telecommunication networks, and emergency services.

The Deep-Shield project addresses this vulnerability by developing an innovative, software-based resilience layer. The system uses advanced deep learning to calculate how trustworthy each satellite signal is in real time, allowing it to distinguish between benign environmental reflections and deliberate cyberattacks. Rather than dropping compromised signals completely, a dynamic navigation engine down-weights unreliable data, enabling continuous and accurate positioning even under active threat.

Compatible with existing GNSS receiver hardware, Deep-Shield will be validated using both simulated and real-world testing scenarios. Ultimately, this project delivers a scalable, cost-effective defense layer to secure critical infrastructure and protect national sovereignty.

Unidentified and unauthorised drones have increasingly been in the news as a potential nuisance and threat; also due to their role in conflicts. Therefore, reliable, easy to use and simultaneously cost-effective interceptor drones are urgently needed. To guide interceptors towards a target drone, the technology of detection, tracking and identification – also from onboard an interceptor – forms a crucial component. Current typically vision-based approaches, however, prove to be unreliable, especially for finding smaller drones, dealing with larger distances, in visually degraded conditions and against a moving background rather than blue sky. “Detect and Track” (D-Track) therefore aims to develop a sensor stack as well as specialised algorithms for more reliable, real-time detection, tracking and identification onboard a flying interceptor drone. The project will investigate the complementary strengths of radar and camera systems to overcome single modality limitations and enable new avenues for interception.

We intend to build a network of wide-angle optical cameras capable of detecting, tracking, and identify uncooperative radio-silent mini-drones in (near) real-time. The multi-viewpoint data will be used to derive 3D (real-world coordinate) flight-paths of anything flying over the camera network and make short-term flight path predictions to allow accurate tracking and identification. The overall objective of this project is to identify the limits of our sensors and techniques under a large variety of conditions, so that it serve as a starting point for follow-up real-life pilot projects and potential integration into a situational awareness monitoring system.

Modern drones are getting harder to catch. Instead of the short-range radio links most counter-drone systems detect, a new breed connects over regular cellular networks (4G/5G) and is flown over the internet—so their signal blends into normal phone traffic and their range is effectively unlimited. This is a growing threat around airports, prisons, borders, and military bases.

We propose a passive detector that quietly listens to cellular signals to spot these drones, without jamming or disrupting nearby phone users. It adds two key capabilities: distinguishing a device flying overhead from one on the ground (using antenna arrays and angle-of-arrival), and continuously tracking a connection rather than only catching it at first contact. Distinctive traffic patterns—like heavy video-streaming uploads—help flag likely drones and trigger a real-time alert.

The project aims to help protect people and critical infrastructure from mini-drones that use infrared (IR) and thermal cameras to find targets at night or in poor visibility. Such drones can be difficult to stop with conventional radio or navigation jamming, especially if they are pre-programmed, fiber-guided, or increasingly autonomous. The project will develop a new type of “visual countermeasure” that does not destroy the drone but confuses its camera system.