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Distributed & Adaptive radar for Drone Monitoring

Opening for: PhD student

The goal of this project is to work towards transitioning radar from a conventional stand-alone sensor to an intelligent and spatially distributed network of cooperative nodes. The spatially distributed aspect will provide information from many partial viewpoints to reconstruct more detailed 3D signatures of the observed scenarios. The intelligent aspect will enable the radar to adapt its parameters and processing to the changes in objects’ behavior and environment, like in a sort of “chess game”. Hence, the intended scientific breakthrough is to formulate, implement, and validate the ‘distributed radar brain’ needed to establish and support this new sensing approach, combining spatially-distributed with adaptive capabilities in radar classification.

Specifically, in this project we work on the problem of monitoring multiple drones that might (or not) act as a coordinated swarm, which is a very timely problem for safety of public spaces and national assets such as airports or stadiums, not just in conflict scenarios but also for every-day monitoring. This problem is scientifically challenging, as drones are relatively small and highly manoeuvrable objects, not easy to track by means of radar sensing especially in an urban environment, and even less easy to understand their intent (e.g., whether they are just accidentally flown where they should not, or if there is an actual malicious intent). Distributed and adaptive radar techniques have the potential to improve our capabilities to monitor these situations, and we seek motivated students to take up this challenge.

During this PhD, you will work in the Microwave Sensing Signals and Systems (MS3) research group at the Department of Microelectronics of TU Delft. Being one of a few European radar groups in academia, this group has extensive research facilities and excellent track record on the full pipeline of microwave and radar sensing, from hardware development to signal processing and automatic object classification. Your direct working environment will include a large pool of PhD students of MS3 (please see our website: radar.tudelft.nl). You will also interact with the partner organizations that are part of the consortium of this project, all leading players in radar systems and related signal processing in the Dutch landscape and beyond. Moreover, in the same project another PhD vacancy is open, for the different application of monitoring human wellbeing.

Your main responsibilities will be to:

• Develop strategies to adapt the configuration of radars in a network and decide the best processing approaches as a function of the object behaviour and changes in the environment, which should be later translated into codes and databases.
• Formulate mathematical models for key radar parameters, feature extraction, and target identification/tracking for drones and drone swarms in heterogeneous radar networks.
• Experimentally validate methods using numerical simulations and in-situ observations.
• Collaborate with another PhD student within the same project to exchange knowledge, perform joint experiments and make sure all project objectives are met.
• Participate in knowledge utilization activities and dissemination of research findings, also including project partners.

Requirements

To be considered for this PhD position you should have:

• A Master's degree in electrical/electronic engineering, computer science, physics, mathematics, or other related fields.
• Knowledge and interest in radar signal processing, preferably but not necessarily in classification techniques and distributed radar systems.
• Knowledge or at least some interest in machine learning, preferably techniques for management/adaptation of systems.
• Programming experience in MATLAB/Python or C/C++, preferably in relation to radar signal processing.
• A curiosity-driven mindset, the ability to learn new things, and a passion for (doing) research. Evidence of innovative thinking and the ability to generate new knowledge is an advantage.  
• An open-minded personality for cooperation with colleagues and co-supervision of students.
• Willingness to help out with education related tasks (e.g., teaching assistance).
• Good English language and communication skills (written and oral) in order to closely cooperate with colleagues and students as well as write project documents.

Due to the envisaged cooperation with project partners, European (EU)/NATO nationality is an advantage.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Contact

dr. Francesco Fioranelli

Associate Professor

Microwave Sensing, Signals and Systems Group

Department of Microelectronics

More information

Additional information

In The Netherlands, almost all PhD positions are linked to funded research projects. This has several implications:

• PhD students are employed: they receive a salary rather than a grant. Most projects have a duration of 4 years.
• Positions become available once a project is funded. This can happen at any time during the year.
• It typically takes 6 to 9 months for a project proposal to receive funding. In this period, a position may be anticipated but the outcome remains insecure. Once a project is funded, the open position needs to be filled as soon as possible.

If you are interested in our research, it merits to inquire whether openings will be available. We collect resumes of prospective PhD students throughout the year, for each of our research tracks.

General requirements

We make our selection based on the following general requirements:

• Formal requirements regarding prior education: you should have earned an MSc degree at a recognized institute for higher education.
• Background: you should have a background that fits the requirements of the project
• Excellence: your Grade-Point-Average should be above 8 (10). Also your MSc thesis should have received a grade above 8 (10).
• English: you should be able to communicate well in english (written and oral). Provide TOEFL/IELTS scores if available.
• Originality: your MSc thesis or later work (publications) should reflect some original ideas. Critical and independent thinking is very important.
• Team player: you should be able to work well in a team of other project members.

Your resume should contain contact information of prior advisors/supervisors who can provide feedback.