Advanced Bayesian computation methods for estimation, prediction and control in multi-sensor complex systems (ADVENTURE). The project will encompass both theoretical and experimental activities. The theory will advance in Bayesian computational tools, with emphasis on filtering and machine learning methods. These new tools can be applied in wireless communications, indoor positioning, or medical applications.
Received Signal Strength-based Indoor Localization using a Robust Interacting Multiple Model-Extended Kalman Filter Algorithm
, International Journal of Distributed Sensor Networks, Vol. 13, No. 8, August 2017.
An Open Path from the Antenna to Scientific-grade GNSS Products
, in Proceedings of the 6th ESA International Colloquium on Scientific and Fundamental Aspects of GNSS / Galileo, 25-27 October 2017, Valencia (Spain).
A Cloud Optical Access Network for Virtualized GNSS Receivers
, Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+), September 2017, Portland, OR.
Air Traffic Radar Interference Event in the Galileo E6 Band: Detection, Analysis and Mitigation
, in Proceeding of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017), 25-26 September 2017, Portland, Oregon (USA).
Uncertainty Exchange through Multiple Quadrature Kalman Filtering
, IEEE Signal Processing Letters, Vol. 23, No. 12, pp. 1825-1829, December 2016.
Uplink FBMC/OQAM-based Multiple Access Channel: Distortion Analysis Under Strong Frequency Selectivity
, IEEE Transactions on Signal Processing, Vol. 64, No. 16, pp. 4260–4272, August 2016.
Vulnerabilities, Threats, and Authentication in Satellite-based Navigation Systems
, Proceedings of the IEEE, Vol. 104, No. 6, pp. 1169-1173, June, 2016.
Universidad Carlos III
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)