Sensors, Thales Nederland B.V., The Netherlands
Information-based Processing in Radar and Communications:
Compressive Sensing and Information Geometry
Compressive Sensing (CS) is a recent paradigm in sensing (since 2004) that works with a reduced number of measurements for a comparable sensing result. It is based on the incoherence of the sensing and sparsity of the processing results. Its major parts are: compressive acquisition and sparse-signal processing. Most promising benefits of CS in radar are resolution and multi-target analysis. Other specific issues in applying CS in radar or communications are: sparse sensing (i.e. design of waveforms and antenna arrays), noise and clutter, grid design and match, real-time implementation, etc.
Information geometry (IG) raises a new approach to stochastic signal processing (since the eighties) as its main principle is that many important structures in the stochastic signal processing can be treated as structures in differential geometry. Most promising benefits of IG have been found in resolution bounds and parameter estimation.
The importance of information in data is stressed in both fields as the useful dimension of signals is much smaller than the data dimensionality. Accordingly, conventional processing can be improved if the demands of data acquisition and signal processing are optimized to the information content (which links it also to the information theory).
CS and IG can also be used in development and understanding of deep learning, especially in the stochastic analysis of the underlying processing layers.
Thales NL proposes an internship project whose aim is to investigate applicability of the information-based processing with emphasis on practical issues in signal processing (SP). Simulated data are to be used to demonstrate the applicability in realistic cases.
Proposed project planning:
- selecting a practical issue and its SP application(s) of interest
- studying IG with emphasis on information specific for (radar/comms) measurements,
- studying CS, radar measurements and their SP,
- (theoretically) investigating the practical link(s) between IG, CS and the application;
- implementing the IG-CS analysis for particular measurements in MATLAB,
- testing and evaluating the IG-CS applicability with simulated data, and
- reporting the IG-CS applicability in the radar/comms SP in a report.
At least five months is preferred (exceptionally at least three months).
Delft, The Netherlands: Advanced Developments group, Thales Nederland B.V.
Profile of candidates
- WO in Electrical Engineering or Applied Mathematics or Applied Physics;
- Strong background in signal processing and geometry;
- Experience in MATLAB;
- Good verbal and written communication skills in English
Contact Details for the Post
If you are interested in this opportunity, please apply by email to: email@example.com mentioning the reference IWP…
Or contact directly the supervisor at Thales NL:
Radmila Pribić, firstname.lastname@example.org