Leuven | More than two weeks ago
Radar is a key technology for applications requiring precise detection in 3D space with a small sensor 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 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.
The large amount of obstacles in the radar environment may produce significant multi-path propagations. This results in the appearance of ghost targets in the radar measurement. The use of multiple radars in different locations can solve this problem and improves the measurement resolution at the same time as each radar has a different view on the environment. In such configuration, each radar can process its own signal (mono-static mode) as well as the echoes of the RF signals sent by other radars (multi-static mode). While the use of multiple radars in mono-static mode is very popular, the combination with multi-static mode is less used, even if it has a great potential, and it is more challenging. Indeed, the performance of multi-static mode strongly depends on the radar synchronization and phase noise of each radar.
Your task will be to investigate how multiple radars can be combined to benefit from mono- and multi- static modes. The student will propose solutions to synchronize radars and propose solutions to compensate for the remaining synchronization errors. Sensors fusion algorithms will also be proposed to combine all radar measurements in a single high-resolution representation of the environment to remove ghost targets due to multi-paths propagations. The proposed solutions will be validated first by simulation then with real radar measurements. For that purpose, two mm-Wave MIMO FMCW (Frequency Modulated Continuous Wave) radars will be used.
You will be part of a large IMEC team working on the research, implementation and prototyping of future radar systems composed by experts in digital and analog mm-wave design and radar signal processing.
The successful candidate must show a strong understanding of signal processing and linear algebra. Proficiency with Matlab or Python is a must. Some knowledge of radar concepts is a plus
- Master Thesis internship (6 months)
- Preceded by optional summer internship (3 months)
Responsible scientist(s): Marc Bauduin (Marc.Bauduin@imec.be)
Type of project: Combination of internship and thesis
Duration: 6 months
Required degree: Master of Engineering Technology, Master of Science, Master of Engineering Science
Required background: Electrotechnics/Electrical Engineering
Supervising scientist(s): For further information or for application, please contact: Marc Bauduin (Marc.Bauduin@imec.be)