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.
Biography
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
- Constrained Infinitesimal Dipole Modeling Assisted Ensemble Prediction of Embedded Element Patterns via Machine Learning
Onat, Nehir Berk; Roldan, Ignacio; Fioranelli, Francesco; Yarovoy, Alexander; Aslan, Yanki;
IEEE Transactions on Antennas and Propagation,
pp. 1-1, 2024. DOI: 10.1109/TAP.2024.3433515 - See Further Than CFAR: a Data-Driven Radar Detector Trained by Lidar
Roldan, Ignacio; Palffy, Andras; Kooij, Julian F. P.; Gavrila, Dariu M.; Fioranelli, Francesco; Yarovoy, Alexander;
In 2024 IEEE Radar Conference (RadarConf24),
pp. 1-6, 2024. DOI: 10.1109/RadarConf2458775.2024.10548426 - Sparse Array Placement for Bayesian Compressive Sensing Based Direction of Arrival Estimation
Lamberti, Lucas L.; Roldan, Ignacio; Yarovoy, Alexander; Fioranelli, Francesco;
In 2024 IEEE Radar Conference (RadarConf24),
pp. 1-6, 2024. DOI: 10.1109/RadarConf2458775.2024.10548658 - Dataset Dependency of Data-Driven ML Techniques in Pattern Prediction Under Mutual Coupling
Onat, N.B.; Roldan, I.; Fioranelli, F.; Yarovoy, A.; Aslan, Y.;
In 2024 4th URSI Atlantic Radio Science Meeting (AT-RASC),
pp. 1-4, 2024. DOI: 10.46620/URSIATRASC24/JMTA5770 - Self-Supervised Learning for Enhancing Angular Resolution in Automotive MIMO Radars
Roldan, Ignacio; Fioranelli, Francesco; Yarovoy, Alexander;
IEEE Transactions on Vehicular Technology,
pp. 1-10, 2023. DOI: 10.1109/TVT.2023.3269199 - Total Variation Compressive Sensing for 3D Shape Estimation in Short-Range Imaging Radars
Roldan, Ignacio; Fioranelli, Francesco; Yarovoy, Alexander;
IEEE Transactions on Radar Systems,
Volume 1, pp. 583-592, 2023. DOI: 10.1109/TRS.2023.3322630 - Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays
Onat, Nehir Berk; Roldan, Ignacio; Fioranelli, Francesco; Yarovoy, Alexander; Aslan, Yanki;
In 2023 17th European Conference on Antennas and Propagation (EuCAP),
pp. 1-5, 2023. DOI: 10.23919/EuCAP57121.2023.10133770 - Low Complexity Single-Snapshot DoA Estimation via Bayesian Compressive Sensing
Roldan, Ignacio; Lamberti, Lucas; Fioranelli, Francesco; Yarovoy, Alexander;
In 2023 IEEE Radar Conference (RadarConf23),
pp. 1-6, 2023. DOI: 10.1109/RadarConf2351548.2023.10149589 - Benchmarking classification algorithms for radar-based human activity recognition.
Fioranelli, Francesco; Zhu, Simin; Roldan, Ignacio;
IEEE Aerospace and Electronic Systems Magazine,
pp. 1-4, 2022. DOI: 10.1109/MAES.2022.3216262 - Enhancing Angular Resolution Using Neural Networks in Automotive Radars
Roldan, Ignacio; Fioranelli, Francesco; Yarovoy, Alexander;
In 2021 18th European Radar Conference (EuRAD),
pp. 58-61, 2022. DOI: 10.23919/EuRAD50154.2022.9784559 - Total Variation Compressive Sensing for Extended Targets in MIMO Radar
Roldan, Ignacio; Fioranelli, Francesco; Yarovoy, Alexander;
In 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM),
pp. 61-65, 2022. DOI: 10.1109/SAM53842.2022.9827822 - 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 - An in-depth noise model for giant magnetoresistance current sensors for circuit design and complementary metal-oxide-semiconductor integration
Roldán, A; Roldán, JB; Reig, C; Cardoso, S; Cardoso, Filipe Arroyo; Ferreira, R; Freitas, PP;
Journal of Applied Physics,
Volume 115, Issue 17, pp. 17E514, 2014.
BibTeX support
Last updated: 23 Sep 2024
Ignacio Roldan
- +31 15 27 82653
- I.RoldanMontero@tudelft.nl
- Room: HB 20.250
- List of publications