Quantum Machine Learning for Doppler Radar Signal Processing in Clutter

Quantum computers are no longer fantasises of distant future. Recent advances in quantum computing hardware as well quantum algorithms offer a wide variety of possibilities to improve existing classical algorithms. Some of the operations involved in the standard classical algorithms might be performed much more efficiently using quantum machines. The current proposal will explore the new possibilities offered by quantum machines for improvements in the areas of radar signal and image processing. This proposal will investigate such possibilities theoretically and will also investigate the practical implementations in present day quantum computers. Thales will utilize the algorithms developed during this project in their machine learning algorithms aimed at defense and civilian applications.

Faculty Supervisor:

Sreeraman Rajan;Bhashyam Balaji

Student:

Partner:

Thales Recherche et Technologie;Thales Canada Inc

Discipline:

Mathematics

Sector:

Manufacturing; Professional, scientific and technical services

University:

Carleton University

Program: