Job description
The focus of this research project is on the optimal design of digital MIMO radar. In this context, we naturally think about the performance bounds of different waveforms in terms of resolution in range, Doppler and angular domains. Furthermore, we also aim at optimal radar design for antenna arrays as well as both the transmitter and the receiver. Finally, adaptivity of the design will be considered.
1. Theoretical bounds
Our optimal MIMO radar design will be guided by certain radar performance criteria. While many research results only use identifiability as a criterium, we want to focus on more specific performance criteria. For instance, target detection probability is a criterium we will investigate, where we can consider either a Neyman Pearson or a Bayesian setting. The actual detection probability might be hard to optimize, but several distances between the probability densities of the two hypotheses (target present or not) can be considered as a manageable proxy. Furthermore, parameter estimation criteria will be considered such as the Fisher information or the Cramér-Rao lower bound, e.g., for estimating the range, Doppler, angle and/or radar cross section. Such criteria will be investigated for static as well as dynamic scenarios, where the latter have the advantage that we can use relatively accurate prior knowledge from past estimates.
2. Optimal radar design
Once we have derived the relevant performance measures, we can start optimizing the radar sequence/frame/antenna structures in order to obtain the best performance under some constraints that limit the amount of resources we are allowed to use (hardware, power, space, etc.). Thereby we will take additional interferences into account, such as self-interference as well as interference from other radars. For a static scenario, we have only a very limited knowledge of the number of targets and their location (e.g., through some rough occupancy maps). For this scenario, we could then for instance fall back to a 2-target approach where we assume 1 target of interest and 1 interfering target that models the total interference term. For a dynamic scenario, however, we will consider a more accurate model since we can obtain a more informative prior from past estimates through a tracker.
3. Closed loop radar
For a dynamic environment, the earlier mentioned optimization should be carried out in an adaptive fashion leading to adaptive resource allocation on both the transmit and receive side. This will naturally require closing the loop, with in this loop both a tracker and a limited capacity feedback channel. We plan to not only select how to adapt the MIMO radar structure based on this feedback, but we will also optimize the type of information that should be sent over the feedback channel, thereby taking the limited capacity into account. Both these tasks will rely on dynamic online optimization theory.
Finally, we want to analyze the performance of all the developed methods. We will therefore focus on simulated yet realistic data. We expect to publish 3-4 journal papers on this topic as well as a number of conference papers.
Job requirements
- An MSc degree in an engineering discipline relevant to the PhD research
- Strong background in linear algebra, signal processing, detection an destimation, and optimization.
- Background in radar and wireless communications is desirable, but not mandatory
- Experience in programming e.g., Python, MATLAB,
- Good verbal and written English skills
- Excellent communication and interpersonal skills
- Ability to work in a collaborative environment
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.
At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.
Challenge. Change. Impact!
Faculty Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.
Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.
Conditions of employment
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2901 per month in the first year to € 3707 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.
Additional information
If you would like more information about this vacancy or the selection procedure, please contact Prof.dr.ir. Geert Leus, via g.j.t.leus@tudelft.nl.
Application procedure
Are you interested in this vacancy? Please apply no later than 23 Mar 2025 via the application button and upload the following documents:
- CV
- Motivational letter
- A detailed list of BSc and MSc courses with grades.
- List of publications.
- Contact information of two references.
You can address your application to Prof.dr.ir. Geert Leus.
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.
Please note:
- You can apply online. We will not process applications sent by email and/or post.
- A pre-employment screening can be part of the selection procedure.
- For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge Security Guidelines. We carry out this check on the basis of legitimate interest.
- Please do not contact us for unsolicited services.
