Artificial Intelligence based Information Fusion in the Universal SDAR

The Master's student will work on the NSERC Discovery Grant Program entitled “Universal Software Defined Avionic Receiver (SDAR) for Robust and Resilient Positioning, Navigation and Timing (PNT)”.

The objectives of this Master’s research include:

  1. Analysis of machine learning, Artificial Intelligence techniques for secured communication and data fusion,
  2. Adaptive multi-SoOP (DME, TMS, 5G, ADS-B) data fusion design based on selected AI methods,
  3. FPGA resources optimization for AI methods implementation within the SDAR platform (PicoDigitizer),
  4. Test and performance analysis in urban and dynamic flight test.

Connaissances requises

The candidate must demonstrate:

  • Excellent background knowledge in aerospace engineering or signal processing field
  • Excellent motivation
  • Good research record and / or good academic curriculum
  • Ability to work well
  • Excellent programming knowledge

Programme d'études visé

Maîtrise avec mémoire

Domaines de recherche

Aérospatiale

Financement

Annual scholarship offered (amount to be specified)

Autres informations

Date de début : 2019-09-01 

Partenaire impliqué : NSERC

Personne à contacter

René Jr Landry | renejr.landry@etsmtl.ca