Title:
Reinforcement learning for predictive wavefront-sensorless optical satellite communication adaptive optics
Agreement Number:
1000618
Agreement Value:
$187,000.00
Agreement Date:
Feb 17, 2023 - Mar 31, 2026
Description:
The Project involves the application of reinforcement learning (RL) techniques for wavefront sensorless adaptive optics systems used in optical satellite communications. A predictive model will be developed to maximize the coupling of a free-space optical beam into a single mode fiber through an array of wavefront correction elements. Unlike typical adaptive optics for astronomy, optical satellite-to-ground communications experience a wide variety of turbulence conditions and can greatly benefit from capturing a coherent optical signal for improved optical channel data throughput, lowered reduce bit-error rates, and reduced emitter laser power requirements. Simulated wavefront distortion will be used to train the model for optimal performance under the dynamic conditions during overhead satellite passes with full wavefront measurement. A trained RL model will provide optimal parameters with existing AO systems and will guide the design of future photonic AO systems for lower cost and improved performance in a variety of ground station locations.
Organization:
National Research Council Canada
Expected Results:
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Location:
Toronto, Ontario, CA M5S 1S8
Reference Number:
172-2022-2023-Q4-1000618
Report Type:
Grants and Contributions
Recipient Business Number:
108162330
Additional Information:
This agreement has been amended 1 time(s) the total amended value is $187,000.The end date of this agreement has been modified by 439 days.
Amendment Date
Feb 24, 2025
Recipient's Legal Name:
The Governing Council of the University of Toronto
Federal Riding Name:
University--Rosedale
Federal Riding Number:
35112
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Purpose:
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.