The sampling theorem defines how a general signal needs to be sampled in order to be represented unambiguously. Compressive sensing uses certain properties in a signal to represent it with fewer samples than the sampling theorem states .
A sensor array is a set of sensors that are spatially distributed in a known pattern in space. Each of the elements in the array, which can be e.g. antennas or microphones, is used for sampling incoming signals. Due to the multiple elements, the sampled signals will not be completely independent, which can be used for spatial filtering  or direction finding , .
We see a potential to use compressive sensing on signals from an antenna arrays , . The aim is to represent the signal in each antenna element with fewer samples than the sampling theorem states. We think that the sample reduction can be both in time and over array elements.
The reduced array signals should still be usable for e.g. direction finding. It is of interest to study how performance is decreased depending on the level of reduction. Other things that can be considered are e.g. how well a method performs at different signal-to-noise ratios, and if signal characteristics other than direction (e.g. frequency, phase modulation) can still be measured after compression.
The end result of this project shall be a written report containing the conclusions from the research.
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You should be highly motivated and be able to work independently. A background in signal processing and interest in linear algebra is an advantage. Also, some knowledge of programming for data analysis, preferably using MATLAB, is required.
This position requires that you will be approved in a security screening in accordance with the Swedish Protective Security Act.
What you will be a part of
The thesis work will be performed at Saab in Järfälla (20 min from central Stockholm). Supervisors at Saab will be
- Thomas Neimert-Andersson, Saab, email@example.com
- Johan Malmström, Saab, firstname.lastname@example.org
The formal examiner will be appointed by the university.
You will join the Business Area Surveillance.
If you aspire to help create and innovate whilst developing yourself in a challenging team setting, 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 help protect people.
1. E. J. Candès, M. B. Wakin, “An introduction to compressive sampling”, IEEE Signal Processing Magazine, vol. 25(2), 2008
2. R. J. Mailloux, Phased Array Antenna Handbook. Artech House, 2005
3. C. A. Balanis, Antenna Theory Analysis and Design. John Wiley & Sons, 2005
4. H. Krim, M. Viberg, “Two decades of array signal processing research: The parametric approach,” IEEE Signal Processing Magazine, 13(4), 1996
5. H. E. A. Laue and W. P. du Plessis, “Numerical Optimisation of Compressive Array Feed Networks,” IEEE Transactions on Antennas and Propagation, vol. 66(7), 2018.
6. W. R. Smith and W. P. du Plessis, “Sample Reduction during Signal Detection Using Difference Sets and Almost Difference Sets,” submitted for publication in IEEE Transactions on Signal Processing.