Leuven | More than two weeks ago
The advent of low-cost and small form factor multi-input multi-output (MIMO) millimeter-wave radar sensors has enabled numerous new applications that are well beyond those that are traditionally associated with radars. Many applications involve the detection, tracking, classification and identification of human beings in indoor or outdoor environments. These radar functionalities pose new challenges with human beings because they are non-rigid bodies and are highly maneuvering objects. In order to better fine-tune these functionalities, good simulation models with realistic radar signatures are needed.
The goal of this Master Thesis is, starting from existing 3D models of human bodies, to refine and integrate them in a complete radar system simulation environment. Doing so, it will be possible to generate raw radar data (i.e ADC samples). It is the ambition that the human body model will be sufficiently accurate to enable the generation of realistic radar data cubes and micro-Doppler signals. These will then be used for different high-level signal processing functionalities such as tracking, micro-Doppler and/or micro-range-based classification, inverse synthetic aperture radar (ISAR) processing, etc...
The work includes:
Learning the human body models available at IMEC.
Learning the radar system simulation environment of IMEC.
Improve the human body model and integrate it in the IMEC radar simulation environment.
Fine tune the and validate the human body model by comparison with real radar captures in controlled environments
The successful candidate must be proficient with Matlab. A good understanding of signal processing is required. Prior knowledge of radar concepts is a plus.
Interested students can already get a feel of the human body model that must be integrated in the radar simulation environment at this link: https://sketchfab.com/tags/mocap
- Master Thesis internship (6 months)
- Preceded by optional summer internship (max 3 months)
Responsible scientist(s): Seyed Hamed Javadi (firstname.lastname@example.org )
Type of project: Combination of internship and thesis
Duration: 6 months
Required degree: Master of Engineering Technology, Master of Engineering Science, Master of Science
Required background: Electrotechnics/Electrical Engineering
Supervising scientist(s): For further information or for application, please contact: Seyed Hamed Javadi (email@example.com)