PhD - Leuven | More than two weeks ago
Radar is a key technology for applications requiring precise detection in 3D space with small sensors, as in autonomous driving cars. Due to their high carrier frequency, mm-wave radars can use large bandwidth, which gives access to high range resolution, and have small antennas, which allows Multiple-Input-Multiple-Output (MIMO) solutions to estimate the angular position of the obstacles. The combination of high range and angular resolution with the ability to measure the Doppler effect provides accurate information on the surrounding environment. But the increasing angular resolution requirements implies an increase in the number of antennas on a single radar sensor which comes with a high cost in hardware resources and power consumption. It is therefore mandatory to drastically reduce the hardware complexity for a given imaging resolution level.
For many applications, multiple radars will be mounted on a moving platform (such as automotive, drone or robotic). The movement of the platform can be used to create a so-called Synthetic Aperture Radar (SAR) to achieve higher resolution with a smaller number of antennas. Recently, SAR processing has also been proposed for forward-looking configurations.
The mission of this PhD is to combine multiple cooperative radars on a single platform to improve the performances of the forward-looking SAR. As the SAR processing is very sensitive to any error in the platform motion estimation, the PhD student will also investigate solutions to reduce the impact of those errors. This will be achieved by optimizing the design of each individual radar as well as the data fusion between each radar measurement. Another complementary approach is to estimate accurately the radar position and velocity during the SAR data collection. In addition, the PhD student will also propose new signal processing and machine learning techniques to improve the resolution of imaging radars way beyond their conventional resolution. The proposed solutions will be validated on mm-wave MIMO radar.
The successful PhD candidate will be part of a large IMEC team working on the research, implementation and prototyping of future radar systems: experts in digital, analog and mm-wave ASIC design, radar systems, radar signal processing and machine learning. This is a unique opportunity to develop innovative, multi-disciplinary technology and shape future radar systems. You will publish your research in top-level journals and conferences.
Required background: Signal processing for wireless (communication or radar). Knowledge in multi-antennas signal processing. Proficiency with Matlab or Python. Some knowledge of radar concepts, optimization algorithms and machine learning is a plus.
Type of work: 10% literature/theory, 70% modelling/simulation, 20% experimental
Supervisor: Hichem Sahli
Daily advisor: Andre Bourdoux, Marc Bauduin
The reference code for this position is 2023-092. Mention this reference code on your application form.