dr. R.T. Rajan

Assistant Professor
Signal Processing Systems (SPS), Department of Microelectronics

PhD thesis (Oct 2016): Relative Space-Time Kinematics of an Anchorless Network
Promotor: Alle-Jan van der Veen

Expertise: Distributed autonomous systems, Positioning Navigation Timing (PNT), Space systems

Themes: Distributed autonomous sensing systems, Signal processing for communication


Dr. Raj Thilak Rajan (S'11-M'17-SM'22) is an assistant professor with the Signal Processing Systems (SPS) group, the Master Coordinator for the Signals and Systems track (MS-EE-S&S) and is the Co-director of the Delft Sensor AI Lab. He received his Ph.D. in 2016 from TUD, and obtained his M.Sc. (class first, youngest in class) and B.Sc. (with distinction) in Electronic sciences from University of Pune, India in 2006 and 2004 respectively.  Raj is an IEEE Senior member, and the Best paper award nominee at IEEE CAMSAP 2013. He is an elected member of the IEEE ASI (Autonomous Systems Initiative) and the IAF SCAN (Space communications and Navigation) committee. He is an Associate Editor for the IEEE Open Journal of Signal Processing (IEEE-OJSP), and is a reviewer for various related journals and conferences. His research interests lie in statistical machine learning and optimization, with applications to distributed autonomous sensing systems.

Previously, he held research positions with diverse responsibilities at IMEC (Eindhoven, 2015-2018), University of Twente (Enschede, 2014-2015) and ASTRON (Dwingeloo, 2008-2014). He was a SSPF fellow (The Netherlands, 2019), INFN fellow (Italy, 2008), MIUR fellow (Italy, 2007), TIFR-VSRP fellow (India, 2005), and is an alumnus of the SSP2019 program from the international space university (ISU). He obtained his University Teaching Qualification (UTQ/BKO) diploma in 2021. 

If you are interested in collaborating on relevant topics, then I look forward to hearing from you. PhD aspirants and enthusiastic master thesis students are encouraged to write to me with a (a) your interests+passion (b) resume and (c) a brief proposal (not for master students). There are numerous internships and thesis oppurtunities with other companies and institutes. If you are already pursuing a thesis/internship/extra-project with me, then you can find guidelines here 

New PhD opening !!!

EE4540 Distributed signal processing

Signal processing techniques for decentralized signal processing

EE4C11 Systems engineering

Introduction to systems engineering processes

ET4386 Estimation and detection

Basics of detection and estimation theory, as used in statistical signal processing, adaptive beamforming, speech enhancement, radar, telecommunication, localization, system identification, and elsewhere.

Education history

EE3350TU Introduction to Radio Astronomy

(not running) Introduction to the science and technology of radio astronomy


Physics inspired inference, classification and prediction in networked systems

Reliable POwerDown for Industrial Drives

The pioneering EU research project R-PODID started on the 1st of September 2023. This KDT JU co-funded project aims to develop an automated, cloudless, short-term fault-prediction for electric drives, power modules, and power devices, that can be integrated into power converters.


Science and technology for Lunar surface missions

Delft Sensor AI Lab

Bringing AI to sensor networks

Cooperative Relative Navigation of Multi-agent Systems

Develop algorithms for multi-target position, time and orientation tracking in a mobile network of multi-agent systems

Airborne data collection on resilient system architectures

Develop algorithms to realize efficient, robust, cost-effective perception and control for autonomous navigation of drones

Projects history

PIPP OLFAR: Breakthrough technologies for Interferometry in Space

Combine multiple satellites into one single scientific instrument: a radio telescope in space

Low-frequency distributed radio telescope in space

Below 15 MHz, the ionosphere blocks EM signals from the sky. Therefore, can we design a radio telescope in space, using a swarm of inexpensive nano-satellites? Accurate localization and clock recovery is important.

  1. Joint Ranging and Phase Offset Estimation for Multiple Drones using ADS-B Signatures
    Mohammadkarimi, Mostafa; Leus, Geert; Rajan, Raj Thilak;
    IEEE Transactions on Vehicular Technology,
    2023. DOI: 10.1109/TVT.2023.3318192

  2. Enabling Technologies for Navigation and Communication of UAS operating in the context of BVLOS
    Politi, Elena; Purucker, Patrick; Larsen, Morten; Dos Reis, Ricardo J; Rajan, Raj Thilak; Penna, Sergio Duarte; Boer, Jan-Floris; Rodosthenous, Panagiotis; Dimitrakopoulos, George; Varlamis, Iraklis; others;

  3. Distributed Gaussian Process Hyperparameter Optimization for Multi-Agent Systems
    Zhai, Peiyuan; Rajan, Raj Thilak;
    In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
    IEEE, pp. 1--5, 2023.

  4. Artificial Potential Field-Based Path Planning for Cluttered Environments
    Diab, Mosab; Mohammadkarimi, Mostafa; Rajan, Raj Thilak;
    In 2023 IEEE Aerospace Conference,
    IEEE, pp. 1--8, 2023.

  5. Distributed Particle Filter Based on Particle Exchanges
    Tang, Rui; Riemens, Ellen; Rajan, Raj Thilak;
    In 2023 IEEE Aerospace Conference,
    IEEE, pp. 1--8, 2023.

  6. Geometry-Aware Distributed Kalman Filtering for Affine Formation Control under Observation Losses
    Li, Zhonggang; Rajan, Raj Thilak;
    In 2023 26th International Conference on Information Fusion (FUSION),
    IEEE, pp. 1--7, 2023.

  7. Decentralized coordination for truck platooning
    Zeng, Yikai; Wang, Meng; Rajan, Raj Thilak;
    Computer-Aided Civil and Infrastructure Engineering,
    2022. DOI: https://doi.org/10.1111/mice.12899

  8. The science case and challenges of space-borne sub-millimeter interferometry
    Leonid I. Gurvits; Zsolt Paragi; Ricardo I. Amils; Ilse {van Bemmel}; Paul Boven; Raj Thilak Rajan; others;
    Acta Astronautica,
    Volume 196, Issue 314-333, 2022. DOI: https://doi.org/10.1016/j.actaastro.2022.04.020

  9. Frequency augumented clock synchronizaion for space-based interferometry
    Felix Abel; Prem Sundaramoorthy; Raj Thilak Rajan;
    In Small Satellite Systems and Services : 4S Symposium,
    ESA/ESTEC, pp. 14, May 2022.

  10. Relative Kinematics Estimation Using Accelerometer Measurements
    Mishra, Anurodh; Rajan, Raj Thilak;
    In 2022 30th European Signal Processing Conference (EUSIPCO),
    IEEE, pp. 1856--1860, 2022.

  11. Distributed kalman filters for relative formation control of multi-agent systems
    Van Der Marel, Martijn; Rajan, Raj Thilak;
    In 2022 30th European Signal Processing Conference (EUSIPCO),
    IEEE, pp. 1422--1426, 2022.

  12. Applications and Potentials of Intelligent Swarms for magnetospheric studies
    Raj Thilak Rajan; Shoshana Ben-Maor; Shaziana Kaderali; Calum Turner; Mohammed Milhim; Catrina Melograna; Dawn Haken; Gary Paul; Vedant; V. Sreekumar; Johannes Weppler; Yosephine Gumulya; Riccardo Bunt; Asia Bulgarini; Maurice Marnat; Kadri Bussov; Frederick Pringle; Jusha Ma; Rushanka Amrutkar; Miguel Coto; Jiang He; Zijian Shi; Shahd Hayder; Dina Saad Fayez Jaber; Junchao Zuo; Mohammad Alsukour; Cécile Renaud; Matthew Chris;
    Acta Astronautica,
    2021. DOI: https://doi.org/10.1016/j.actaastro.2021.07.046
    Keywords: ... Satellite swarms, Intelligent swarms, Heliophysics, Magnetosphere, Cubesats, Next generation space systems.

    Abstract: ... Earth’s magnetosphere is vital for today’s technologically dependent society. To date, numerous design studies have been conducted and over a dozen science missions have flown to study the magnetosphere. However, a majority of these solutions relied on large monolithic satellites, which limited the spatial resolution of these investigations, as did the technological limitations of the past. To counter these limitations, we propose the use of a satellite swarm carrying numerous and distributed payloads for magnetospheric measurements. Our mission is named APIS — Applications and Potentials of Intelligent Swarms. The APIS mission aims to characterize fundamental plasma processes in the Earth’s magnetosphere and measure the effect of the solar wind on our magnetosphere. We propose a swarm of 40 CubeSats in two highly-elliptical orbits around the Earth, which perform radio tomography in the magnetotail at 8–12 Earth Radii (RE) downstream, and the subsolar magnetosphere at 8–12 RE upstream. These maps will be made at both low-resolutions (at 0.5 RE, 5 s cadence) and high-resolutions (at 0.025 RE, 2 s cadence). In addition, in-situ measurements of the magnetic and electric fields, plasma density will be performed by on-board instruments. In this article, we present an outline of previous missions and designs for magnetospheric studies, along with the science drivers and motivation for the APIS mission. Furthermore, preliminary design results are included to show the feasibility of such a mission. The science requirements drive the APIS mission design, the mission operation and the system requirements. In addition to the various science payloads, critical subsystems of the satellites are investigated e.g., navigation, communication, processing and power systems. Our preliminary investigation on the mass, power and link budgets indicate that the mission could be realized using Commercial Off-the-Shelf (COTS) technologies and with homogeneous CubeSats, each with a 12U form factor. We summarize our findings, along with the potential next steps to strengthen our design study.


  13. A roadmap towards a space-based radio telescope for ultra-low frequency radio astronomy
    M.J. Bentum; M.K. Verma; R.T. Rajan; A.J. Boonstra; C.J.M. Verhoeven; E.K.A. Gill; A.J. {van der Veen}; H. Falcke; M. Klein Wolt; B. Monna; S. Engelen; J. Rotteveel; L.I. Gurvits;
    Advances in Space Research,
    Volume 65, Issue 2, pp. 856-867, 2020. High-resolution space-borne radio astronomy. DOI: 10.1016/j.asr.2019.09.007

  14. Lunar Orbit Design of a Satellite Swarm for Radio Astronomy
    Mok, Sung-Hoon; Guo, Jian; Gill, Eberhard; Rajan, Raj Thilak;
    In 2020 IEEE Aerospace Conference,
    pp. 1-9, 2020. DOI: 10.1109/AERO47225.2020.9172468

  15. Autonomous Mission Planning for OLFAR: A Satellite Swarm in Lunar Orbit for Radio Astronomy
    Mok, S; Guo, J; Gill, EKA; Rajan, RT;
    In 71st International Astronautical Congress (IAC),
    IAF/AIAA, 2020.

  16. APIS: Applications and Potentials of Intelligent Swarms for magnetospheric studies
    R.T. Rajan; S. Ben-Maor; S. Kaderali; Others;
    In 71th International Astronautical Congress (IAC),

  17. End-of-life of satellite swarms
    Turner, Calum; Raj Thilak Rajan;
    In 71st International Astronautical Congress (IAC),
    IAF/AIAA, 2020.

  18. Relative kinematics of an anchorless network
    R. T. Rajan; G. Leus; A.J. van der Veen;
    Signal Processing,
    Volume 157, pp. 266-279, April 2019. ISSN: 0165-1684. DOI: 10.1016/j.sigpro.2018.11.005

  19. Low-frequency observations using high-altitude balloon experiments (LOBE)
    Raj Thilak Rajan; P.Sundaramoorthy; C.J.C.Vertegaal; A.Montagne; V.Karunanithi; M.K.Verma; M.Bentum; C.Verhoeven;
    In 70th International Astronautical Congress (IAC),
    IAF, October 2019.

  20. High Data-Rate Inter-Satellite Link (ISL) For Space-Based Interferometry
    Visweswaran Karunanithi; Raj Thilak Rajan; P.Sundaramoorthy; M.K.Verma; C.Verhoeven; M. Bentum; E.W. McCune;
    In 70th International Astronautical Congress (IAC),
    IAF, October 2019.

  21. Multiresolution Time-of-arrival Estimation from Multiband Radio Channel Measurements
    T. Kazaz; R.T. Rajan; G.J.M. Janssen; A.J. van der Veen;
    In 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
    Brighton, UK, IEEE, pp. 4395-4399, May 2019. ISBN: 978-1-4799-8132-8. DOI: 10.1109/ICASSP.2019.8683601

  22. Reference-Free Calibration in Sensor Networks
    Raj Thilak Rajan; Rob-van Schaijk; Anup Das; Jac Romme; Frank Pasveer;
    IEEE Sensor letters,
    Volume 2, Issue 3, pp. 1-4, Sept. 2018. DOI: 10.1109/LSENS.2018.2866627

  23. Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout
    Anup Das; Paruthi Pradhapan; Willemijn Groenendaal; Prathyusha Adiraju; Raj Thilak Rajan; Francky Catthoor; Siebren Schaafsma; Jeffrey L. Krichmar; Nikil Dutt; Chris {Van Hoof};
    Neural Networks,
    Volume 99, pp. 134-147, 2018. DOI: https://doi.org/10.1016/j.neunet.2017.12.015
    Keywords: ... Electrocardiogram (ECG), Spiking neural networks, Liquid state machine, Spike timing dependent plasticity (STDP), Homeostatic plasticity, Fuzzy c-Means clustering.

    Abstract: ... Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach lies in (1) encoding spatio-temporal properties of ECG signals directly into spike train and using this to excite recurrently connected spiking neurons in a Liquid State Machine computation model; (2) a novel learning algorithm; and (3) an intelligently designed unsupervised readout based on Fuzzy c-Means clustering of spike responses from a subset of neurons (Liquid states), selected using particle swarm optimization. Our approach differs from existing works by learning directly from ECG signals (allowing personalization), without requiring costly data annotations. Additionally, our approach can be easily implemented on state-of-the-art spiking-based neuromorphic systems, offering high accuracy, yet significantly low energy footprint, leading to an extended battery-life of wearable devices. We validated our approach with CARLsim, a GPU accelerated spiking neural network simulator modeling Izhikevich spiking neurons with Spike Timing Dependent Plasticity (STDP) and homeostatic scaling. A range of subjects is considered from in-house clinical trials and public ECG databases. Results show high accuracy and low energy footprint in heart-rate estimation across subjects with and without cardiac irregularities, signifying the strong potential of this approach to be integrated in future wearable devices.


  24. A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods
    Xie, Xingzhe; Semanjski, Ivana; Gautama, Sidharta; Tsiligianni, Evaggelia; Deligiannis, Nikos; Rajan, Raj; Pasveer, Frank; Philips, Wilfried;
    ISPRS International Journal of Geo-Information,
    Volume 6, Issue 12, pp. 389, Dec 2017. DOI: 10.3390/ijgi6120389

  25. Data-driven modeling techniques for indoor CO2 estimation
    Vergauwen, Bob; Agudelo, Oscar Mauricio; Rajan, Raj Thilak; Pasveer, Frank; De Moor, Bart;
    In 2017 IEEE SENSORS,
    pp. 1-3, 2017. DOI: 10.1109/ICSENS.2017.8234156

  26. Relative Space-Time Kinematics Of an Anchorless Network
    R.T. Rajan;
    PhD thesis, TU Delft, Fac. EEMCS, October 2016.

  27. Joint ranging and synchronization for an anchorless network of mobile nodes
    R.T. Rajan; A.J. van der Veen;
    IEEE Tr. Signal Processing,
    Volume 63, Issue 8, pp. 1925--1940, April 2015.

  28. Joint relative position and velocity estimation for an anchorless network of mobile nodes
    R.T. Rajan; G. Leus; A.J. van der Veen;
    Signal Processing,
    Volume 115, pp. 66-78, October 2015. DOI: 10.1016/j.sigpro.2015.02.023

  29. Space-based Aperture Array For Ultra-Long Wavelength Radio Astronomy
    R.T. Rajan; A.J. Boonstra; M. Bentum; M. Klein-Wolt; F. Belien; M. Arts; N. Saks; A.J. van der Veen;
    Experimental Astronomy,
    December 2015. DOI: 10.1007/s10686-015-9486-6

  30. Joint Clock Synchronization and Ranging: Asymmetrical Time-stamping and Passive Listening
    S.P. Chepuri; R.T. Rajan; G. Leus; A.J. van der Veen;
    IEEE Signal Processing Letters,
    Volume 20, Issue 1, pp. 51-54, January 2013.

  31. Synchronization for space based ultra low frequency interferometry
    R.T. Rajan; M.J. Bentum; A.J. Boonstra;
    In IEEE Aerospace Conference,
    Big Sky, Montana, US, IEEE, March 2013.

  32. Distributed correlators for Interferometery in space
    R.T. Rajan; M.J. Bentum; A. Gunst; A.J. Boonstra;
    In IEEE Aerospace Conference,
    Big Sky, Montana, US, IEEE, March 2013.

  33. Joint Non-Linear Ranging and Affine Synchronization Basis for a Network of Mobile Nodes
    R.T. Rajan; A.J. van der Veen;
    In Proc. 21st European Signal Processing Conference (EUSIPCO),
    Marrakech (Marokko), September 2013.

  34. Relative velocity estimation using Multidimensional Scaling
    R.T. Rajan; G.J.T. Leus; A.J. van der Veen;
    In Proc. 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2013),
    St. Maarten (Dutch Antilles), December 2013.

  35. The Road To OLFAR - A Roadmap To Interferometric Long-Wavelength Radio Astronomy Using Miniaturized Distributed Space Systems
    S. Engelen; K.A. Quillien; C. Verhoeven; A. Noroozi; P. Sundaramoorthy; A.J. van der Veen; R.T. Rajan; A.J. Boonstra; M. Bentum; A. Meijerink; A. Budianu;
    In IAC 2013,
    Beijing, China, September 2013.

  36. Joint motion estimation and clock synchronization for a wireless network of mobile nodes
    R.T. Rajan; A.J. van der Veen;
    In Proc. IEEE ICASSP,
    Kyoto (Japan), IEEE, pp. 2845-2848, May 2012.

  37. Orbiting Low Frequency Antenna Array for Radio Astronomy
    R.T. Rajan; S. Engelen; M.J. Bentum; C.J.M. Verhoeven;
    In IEEE Aerospace Conference,
    Montana, USA, pp. 1-11, March 2011. DOI: 10.1109/AERO.2011.5747222

  38. Joint ranging and clock synchronization for a satellite array
    R.T. Rajan; A.J. van der Veen;
    In Proc. SPAMEC,
    Cluj-Napoca (Romania), Eurasip, August 2011.

  39. Joint ranging and clock synchronization for a wireless network
    R.T. Rajan; A.J. van der Veen;
    In 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),
    Puerto Rico, IEEE, pp. 297-300, December 2011. ISBN 978-1-4577-2103-8.

  40. OLFAR, Adaptive topology for satellite swarms
    A. Budianu; R.T. Rajan; S. Engelen; A. Meijerink; C.J.M. Verhoeven; M.J. Bentum;
    In IAC 2011,
    Cape Town, October 2011.

BibTeX support

Last updated: 12 Mar 2024