Synthetic Aperture Radar for Automotive Applications

The usability of radars as imagers in modern autonomous vehicles has seen a significant increase in the past two decades toward achieving full autonomy. Mainly, millimeter-wave imagers are better than optical imagers when it comes to the all-weather operation capability as well as the ambient-light independence. However, conventional mm-wave radars require a large number of antenna elements to achieve descent angular resolution. A solution to reduce the required number of antenna elements is to use the motion of the vehicle to take snapshots at different positions and combine them later. This concept is called Synthetic Aperture Radar (SAR), as the motion of the vehicle is used to emulate the presence of a larger number of antenna elements while the real number of antennas on the radar is very low. This synthetic array can produce high-resolution images of the environment.

Unfortunately, the non-ideal motion of the car (e.g. vibration) as well as the motion of the obstacles in the environment degrade the performances of conventional SAR algorithms. Your task will consist of evaluating the limitations of conventional SAR processing and proposing new algorithms to produce high-resolution radar images. The proposed solution will be validated by simulation and processing of real datasets.

Type of work: Modelling, simulation, and signal processing.

You will be part of a large IMEC team working on the research, implementation, and prototyping of future radar systems composed of experts in digital and analog mm-wave design, radar and wireless communication systems, and 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.

Type:

• Master Thesis internship (6 months)
• Preceded by optional summer internship (3 months)