Description:
Sensrad AB offers the highest native-resolution automotive radar on the market named Hugin D1. We operate outside the traditional automotive market offering perception support for Unmanned Ground Vehicles traffic management defence & security and similar domains. The radars current azimuth and elevation resolution is given by the size of the antenna aperture and the number of channels. With this Master Thesis Work we wish to gain insights into ways of increasing the target separability in both dimensions without altering the hardware.
Scope:
The work is focused on the implementation and evaluation of state-of-the-art super-resolution techniques applied to radar point-cloud data from the Hugin D1 radar sensor. By means of advanced algorithms the goal is to increase target separability at the point cloud level potentially only within a defined region of interest while maintaining real-time performance. The motivation is to improve the tracking odometry and mapping capabilities of the radar data from Hugin D1.
A key aspect of this work will be exploring the trade-off between algorithmic complexity and implementation feasibility on a target embedded processor.
The thesis will involve both data acquisition campaigns with Hugin D1 as well as simulation-based data generation if/when needed. The successful candidate will contribute to advancing radar perception performance in next-generation Hugin D1.
Responsibilities:
- Evaluate state-of-the-art super-resolution methods for radar point cloud data.
- Adapt algorithms suitable for real-time DSP implementation.
- Perform radar data acquisition and data point simulations.
- Analyze performance metrics e.g. separability as function of angle latency failure modes such as missed targets and resource utilization.
- Present and demo the work to the company.
Qualifications:
- MSc student in Electrical Engineering Applied Physics Computer Science or similar field.
- Strong background in signal processing preferably radar signal processing.
- Experience with Python programming.
- Knowledge of signals and systems.
- Experience with embedded systems and/or DSPs is meriting.
- High academic performance is meriting.
Start date:
Beginning of 2026 (or upon agreement)
Location:
Sensrad AB Falkenbergsgatan 3 Gothenburg Sweden.
Application:
Through the website. Applications will be reviewed continuously.
Description:Sensrad AB offers the highest native-resolution automotive radar on the market named Hugin D1. We operate outside the traditional automotive market offering perception support for Unmanned Ground Vehicles traffic management defence & security and similar domains. The radars current azimu...
Description:
Sensrad AB offers the highest native-resolution automotive radar on the market named Hugin D1. We operate outside the traditional automotive market offering perception support for Unmanned Ground Vehicles traffic management defence & security and similar domains. The radars current azimuth and elevation resolution is given by the size of the antenna aperture and the number of channels. With this Master Thesis Work we wish to gain insights into ways of increasing the target separability in both dimensions without altering the hardware.
Scope:
The work is focused on the implementation and evaluation of state-of-the-art super-resolution techniques applied to radar point-cloud data from the Hugin D1 radar sensor. By means of advanced algorithms the goal is to increase target separability at the point cloud level potentially only within a defined region of interest while maintaining real-time performance. The motivation is to improve the tracking odometry and mapping capabilities of the radar data from Hugin D1.
A key aspect of this work will be exploring the trade-off between algorithmic complexity and implementation feasibility on a target embedded processor.
The thesis will involve both data acquisition campaigns with Hugin D1 as well as simulation-based data generation if/when needed. The successful candidate will contribute to advancing radar perception performance in next-generation Hugin D1.
Responsibilities:
- Evaluate state-of-the-art super-resolution methods for radar point cloud data.
- Adapt algorithms suitable for real-time DSP implementation.
- Perform radar data acquisition and data point simulations.
- Analyze performance metrics e.g. separability as function of angle latency failure modes such as missed targets and resource utilization.
- Present and demo the work to the company.
Qualifications:
- MSc student in Electrical Engineering Applied Physics Computer Science or similar field.
- Strong background in signal processing preferably radar signal processing.
- Experience with Python programming.
- Knowledge of signals and systems.
- Experience with embedded systems and/or DSPs is meriting.
- High academic performance is meriting.
Start date:
Beginning of 2026 (or upon agreement)
Location:
Sensrad AB Falkenbergsgatan 3 Gothenburg Sweden.
Application:
Through the website. Applications will be reviewed continuously.
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