Grants and Contributions

Titre: ICEBERG

Put in place a Web platform for client orders to optimize imagery processing and classification.

Title: Automated plume detection algorithm for high-resolution methane measurements from GHGSat satellites

Develop a new AI algorithm to detect methane emissions plumes measured by GHGSat's satellites, with little or no human intervention.

Title: Cloud-Based Delivery of Space-Based Analytics

Build a cloud-based computing architecture that reliably predicts the costs for space data storage, delivery and use of cloud-based data analytics for projects of varying sizes.

Title: Automated Monitoring of Reclamation Status using Remote Sensing and Artificial Intelligence

Develop new services in the areas of EO and AI for the natural resource development and oil and gas industry.

Title: Improving Space-Based Radar Reflectometry for Better Ocean State and Target Monitoring Using Advanced Data Processing

Improve the performance of space-based radar reflectometry for ocean-surface target monitoring by using state-of-the-art data processing technology.

G-iCMPS will be a generic, highly configurable, AI-enabled, cloud-based, multi-objective mission planning and task scheduling system for almost any Earth observation constellation (real or virtual) with homogenous or heterogeneous combination of SAR, AIS, EO/IR, and MSS payloads and with satellites capable of performing active attitude maneuvers (slews).

CAUSAL ANALYSIS OF CARDIORESPIRATORY COUPLING ON THE ISS
Astronauts face many challenges (space walks) due to the harsh space environment. Proper functioning of heart, lungs, and circulation is required to support these activities, but physical activity becomes more difficult with longer missions. Weightlessness weakens bones, muscles, heart, and blood circulation. Therefore, the ability to monitor vital life signs is important to see if any changes could be life threatening. This study will investigate our new analysis techniques to detect negative effects on the interaction of the heart, lungs and circulation through real-time monitoring with the Bio-M. We will observe astronauts as they exercise before, during and after spaceflight.

Space agencies, research institutes and private organizations are looking for commercial landing services in order to reach sites of interest on the Moon. The landing systems will need to be equipped with high-accuracy navigation systems to accurately reach their target. Since there is no GPS constellation around the Moon for real-time localisation, or other readily available commercial systems to answer this need, a novel approach is needed to provide positioning of orbiters or landers around the Moon.

The “Crater-Based Absolute Navigation Demonstration” project aims at filling this need by demonstrating a GPS-like system in support for future Moon exploration missions. This system will use features on the ground – Moon craters – as references to autonomously determine the position of orbiters and landers in Moon geographical coordinates. This will increase the accuracy at touchdown by orders of magnitude with respect to current capabilities and help meet the challenging requirements of future Moon precision landing missions.

It will serve as the first known in-space demonstration of a deep learning algorithm operating on the surface of the Moon.

Situational awareness is a key capability required by most modern exploration missions today. Government and commercially-leveraged missions alike increasingly need more compact, affordable imaging systems capable of delivering a range of data products. At the same time, mission constraints drive a need for improved onboard processing, autonomy and artificial intelligence to minimize volume of Earth-Moon data transfer, all while keeping costs low.

This project aims to address these needs and challenges via demonstration and performance characterization of a Smart Lunar Vision System and its different functionalities ahead of future applications in human and robotic exploration. The system developed by Canadensys features a low-mass, low power 360° imaging system, with applications spanning Low Earth Orbit (LEO), Medium Earth Orbit (MEO) and Geostationary Earth Orbit (GEO) out to the Moon, Mars and beyond. The LEAP Capability Demonstration project builds flight heritage for the system in cislunar space, ensuring a system that is both operationally ready and commercially competitive.