Christian Doppler Laboratory for Location-aware Electronic Systems
- 2019 — 2025
- Christian Doppler Research Association (CDG), Boltzmanngasse 20, 1090 Vienna, Austria
- SES Imagotag GmbH, Kalsdorfer Straße 12, 8072 Fernitz-Mellach, Austria
- NXP Semiconductors Austria GmbH, Mikron-Weg 1, 8101 Gratkorn, Austria
- Vienna University of Technology, Gußhausstraße 25/354, 1040 Wien, Austria
- Research Areas
- Klaus Witrisal
- Holger Arthaber (TU Wien)
- Stefan Grebien
- Daniel Neunteufel (TU Wien)
- Lukas Wielandner
- Alexander Venus
- Andreas Fuchs
- Stefan Hechenberger (TU Wien)
The Christian Doppler Laboratory for Location-Aware Electronic Systems has the long-term vision of investigating fundamental limitations of location-aware electronic systems and creating and validating key algorithm solutions and transducer hardware designs for it.
Localization is a key feature of current and future electronic systems. It is often a profound challenge to reach the desired levels of robustness, accuracy, timeliness, and efficiency, targeting at a wide range of end-user applications, potentially with mission-critical performance requirements such as, e.g., in autonomous driving. In addition, emerging location-based and location-aware systems are based on very heterogeneous technology platforms, ranging from RFID transponders to smart phones and self-driving cars.
Research of past decades on global navigation satellite systems (GNSS) has shown that the rigorous modeling of physical influences in combination with exploitation of side-channel information can yield excellent performance for a huge set of practical applications. The proposed CD-Laboratory aims at addressing in a systematic way those application domains that go beyond the physical limits of GNSS, for instance indoor scenarios. The investigated sensing technologies will be focused on radio systems but include also, e.g., optical systems, ultrasound, and inertial sensing units.
The design of electronic systems for positioning is a multi-disciplinary challenge rooted in telecommunications engineering, requiring insight in disciplines such as electronics and microwave engineering, wireless communications, signal processing, estimation and detection theory, Bayesian inference, propagation channel modeling, and machine learning. The proposed approach extends from the modeling of sensing signals and signal transducers, via transducer adaptation and sensor data fusion, to the modeling of environment properties, aiming at a fully cognitive sensing system that provides location awareness to services building upon this sensing platform.