Microwave Sensing, Signals and Systems
Department of Microelectronics

MSc I Roldan

Researcher
Microwave Sensing, Signals and Systems (MS3), Department of Microelectronics

Expertise: Digital signal processing focused on radar signals; Machine Learning applied to detection and classification.

Themes: Distributed sensor systems, Radar for Remote Sensing and Targets Characterization, Radar technology

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.

He successfully completed his PhD on the 18th of November 2024, with his thesis available here and the dataset generated by this work also available here.

Doppler-free classification for automotive radar

  1. Automatic Labelling & Semantic Segmentation with 4D Radar Tensors
    Sun, Botao; Roldan, Ignacio; Fioranelli, Francesco;
    In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
    pp. 1-5, 2025. DOI: 10.1109/ICASSP49660.2025.10890149

  2. 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

  3. A Deep Automotive Radar Detector using the RaDelft Dataset
    Roldan, Ignacio; Palffy, Andras; Kooij, Julian F. P.; Gavrila, Dariu M.; Fioranelli, Francesco; Yarovoy, Alexander;
    IEEE Transactions on Radar Systems,
    pp. 1-1, 2024. DOI: 10.1109/TRS.2024.3485578

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

BibTeX support

Last updated: 21 Jan 2025

Ignacio Roldan

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