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Master thesis 30 hp: Signal detection using digital antenna arrays with machine learning

Järfälla, Sweden
Closing date
15 December 2021
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Saab Electronic Warfare and Aircraft Systems (EWAS) develop systems processing wideband radio signals using antenna arrays. Typically, these systems are designed for detecting radar pulses. However, as the signal environment is becoming more complex, more than just radar pulses will find their way into the receiving system.

Description of the master thesis

Detecting, classifying and localizing the direction of arrival of these complex signals are critical tasks that likely can be solved using object detection based methods, which recently have seen a remarkable progress in the field of computer vision. In this master thesis, we would like to investigate machine learning based methods for simultaneous detection, classification, and localization of signals in an array of sampling elements (such as antennas or microphones).

Specifically, in this master’s thesis you will create a model for the receiving array, and synthetically place a radar in one angle of arrival, and a white noise jammer in another angle of arrival. The radar itself might emit “regular” pulses, or waveforms that are more complicated. How well does your algorithm detect the signals emitted from the radar? How close can the radar be to the jammer, and still be detected?

The algorithm itself could likely be machine/deep learning based.

Your profile

We are looking for 1-2 students (30 HP each) who:

  • Are at the end of their master’s degree in Electrical Engineering, Applied Physics, Computer Science, or similar.
  • Have an interest in signal processing and machine learning.
  • Have taken courses related to machine learning, deep learning, and signal processing.

Start January 2022, or according to agreement.

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.

Last application date



Eric Norgren

Alexander Karlsson

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.