MSc I Roldan
Microwave Sensing, Signals and Systems (MS3), Department of Microelectronics
Expertise: Digital signal processing focused on radar signals; Machine Learning applied to detection and classification.
Ignacio Roldan received his B.Sc. and M.Sc. in Telecommunication Engineering at the Universidad Politecnica de Madrid, Spain in 2014 and 2016. In 2018 he complemented his education with an M.Sc. in Signal Processing and Machine Learning at the same university. Ignacio has worked more than 5 years for Advanced Radar Technologies, a Spanish tech company focused on the design and manufacture of radar systems. In this period, he has been involved in several international projects developing state-of-the-art signal processing techniques for radars. In his last stage, he was focused on applying Machine Learning techniques to UAV detection and classification. In Sep 2020, he joined the Microwave Sensing, Signals, and Systems group at Delft University of Technology as a Ph.D. candidate.
Doppler-free classification for automotive radar
- DopplerNet: a convolutional neural network for recognising targets in real scenarios using a persistent range–Doppler radar
I. Roldan; C. R. del-Blanco; Á. Duque de Quevedo; F. Ibañez Urzaiz; J. Gismero Menoyo; A. Asensio López; D. Berjón; F. Jaureguizar; N. García;
IET Radar, Sonar Navigation,
Volume 14, Issue 4, pp. 593-600, 2020. DOI: 10.1049/iet-rsn.2019.0307
Last updated: 17 Feb 2022