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Master Thesis, 30 hp: Low Footprint Multi Hypothesis Tracker for small Radar Sensors

Location
Järfälla, Sweden
Closing date
31 January 2022
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Background

SAAB has developed a line of small Doppler radar sensors to be used in civil security and traffic supervision applications.

The received echoes from a radar must compete with noise, unwanted echoes, clutter, and interference from other signal sources.

To increase accuracy and sensitivity of these sensors some form of data association is needed to combine several low confidence radar detection's into high confidence tracks.

Data associations are made on the attributes of the detection's such as position, Doppler and amplitude.

Multiple hypothesis tracking (MHT) is generally accepted as the preferred method for solving the data association problem in modern multiple target tracking (MTT) systems.

Today many MTT solutions requires a relatively large amount of computational power and memory which makes them unsuitable for use in a small embedded system.

Description of the master thesis

This project shall study techniques of associating and combining radar detections into tracks and do it in a way that is suitable for use in a small low power single core computer.

The project shall include the study of different MTT techniques and suggest possible solutions suitable for small low power systems.

The main tasks of the project are:

  • Conducting literature survey on the key technologies.
  • Suggest a number of possible solutions and implement these in Matlab.
  • Compare the solutions when run with simulated input data and/or detection data from a real radar sensor.
  • Optionally implement an MTT in a radar sensor and conduct practical tests.
  • Writing of your Master’s thesis including a summary of conclusions and recommendations for future work
  • Presentation of your Master’s thesis

Your profile

Required skills:

  • Successfully completed (or nearly finished) university level studies in Degree of Science in Engineering towards Engineering Physics, Electrical Engineering or Computer Engineering
  • Good skills of Digital Signal Processing
  • Good skills in programming (Matlab)
  • Good skills in programming (C/C++)

Desired skills:

  • Embedded SW development.
  • Statistical theory and methods.
  • Experience working in a lab environment

This position requires that you pass a security vetting based on the current regulations around/of security protection. For positions requiring security clearance additional obligations on citizenship may apply.

Contact

Joel Midstjärna

joel.midstjarna@saabgroup.com

Last application day

2022-01-31

Kindly observe that this is an ongoing recruitment process and that the position might be filled before the closing date of the advertisement.

If you aspire to help create and innovate whilst developing yourself in a learning culture, Saab may well have the perfect conditions for you to grow. We pride ourselves on a nurturing environment, where everyone is different yet we share the same goal – to keep people and society safe.