Format: 2023
Format: 2023
Format: 2023
1516 results found
Data compression as a service

Telemetry data is the most valuable asset provided by any spacecraft. Increasing the data amount sent from space to ground increases a mission’s value, but often this comes with increased costs. Compression of Space generated data provides great benefits to both the large ESA missions by increasing the mission science throughput and small missions (which typically have low bandwidth) by increasing the traditional low downlink rates of these missions. One solution to this problem is the POCKET+ lossless compression algorithm, which is currently being standardized by CCSDS.



VisionSpace Technologies


Cubesats have the potential to revolutionize Earth Observation by exploring different operating points in terms of spatial, temporal, and spectral resolution. However, physical limitations, mostly in terms of size, prevent them from obtaining high-quality images. OPS-SAT, while characterized by a small form factor, provides an impressive in terms of capabilities and flexibility hardware/software platform for executing demanding machine learning algorithms (inference stage).



OHB Hellas

A Consumable-less Propulsion System Based on a Bare-Photovoltaic Tether

As proved in several missions, the Lorentz force acting on the electric current carried by a space ElectroDynamic Tether (EDTs) can be used to propel spacecraft without using propellant. State of the art EDTs involve a bare tape for passive electron collection (anodic contact) and an active device, or a tether segment coated with a low-work-function material, for electron emission (cathodic contact).


ETD 2021-04

Universidad Carlos III de Madrid

A Constellation of Nanosatellites around the Sun

The Sun regularly releases considerable amounts of energy resulting in coronal mass ejections (CMEs) and accelerated particles, which can have a variety of adverse space weather (SW) effects at Earth and in the near-Earth environment. A useful means of tracking SW activity is via solar radio bursts (SRBs) associated with CMEs and solar energetic particle events (SEPs); CME-driven shocks can be tracked via Type II SRBs, while energetic electrons escaping into the heliosphere can be tracked via Type III SRBs.



Dublin Institute for Advanced Sciences

A Comparative Study Of High-Level And Low-Level Implementations Of Deep Learning Models For Spacecraft

Mission Control deployed a low-level implementation of the OPS-SAT SmartCam model using a Field Programmable Gate Array (FPGA), comparing against a high-level CPU model using Tensorflow Lite. Experiments showed that the FPGA implementation reproduced the precision and accuracy of the high-level model, while running at a slower speed. Further optimizations of the FPGA are expected to close the gap in timing and unlock new methods for deploying deep learning on spacecraft.



Mission Control Space Services

LEO-GEO for Greenhouse Gases LEO-GEO4GHG

LEO-GEO4GHG studies the feasibility of new frontiers of Cloud Computing in Space and artificial intelligence (AI) combining multiple sources of data such as SATLANTIS GEI-SAT constellation and other external meteorological and atmospheric data with the final aim of providing near real time methane detection and quantification.




NEU4SST - Neuromorphic Processing for Space Surveillance and Tracking

In this project the authors look at event-based sensing and processing for space situational awareness (SSA). Many advantages exist with the new paradigm of neuromorphic engineering, the authors investigate: If event-based optical data is suitable for the task and if processing with Spiking Neural Networks (SNN) provides advantages in terms of efficiency and efficacy. With the implementation of a novel heterogeneous LIF SNN, authors claim to surpass the state of the art in event-based SSA with a 15% increase in accuracy.

United Kingdom



Blockchain ecosystem for an autonomous consensus mechanism of federated satellite networks – Space DAO

In applications such as space traffic and disaster response management, there are growing public and private capabilities. Multiple different stakeholders can detect and identify events (space collision predictions, natural disaster definitions). Augmentation of events definitions lead to confusion for local authorities, operators or any users of these information for costly decisions. This project, Space DAO, sets the base infrastructure to agree on consensus mechanisms to reduce confusion and augment trust in key decision making information.



Hybrid Edge-Cloud AI Accelerated Astrometric Reduction Pipeline for Agile Near-Real Time In-Situ Space Surveillance and Tracking

With the “democratisation of space”, and the proliferation of large non-geostationary orbit (NGO) constellations, the pace at which human-made objects are being deployed in orbit demands urgent action in defining and supporting a global Space Traffic Management (STM) plan. Promptly identifying, tracking, and cataloguing of resident space objects (RSOs), in particular after orbit insertion or break-up and fragmentation events, as the recent Russian anti-satellite weapon (ASAT) test put in evidence, is of critical importance to enable a safe and sustainable use of space.





A proof of concept of an attitude control system based on Artificial Intelligence, as an alternative of current state-of-the-art systems based on model approaches, has been developed and tested in a simulator and in the EM of the OPS-SAT. The system relies on Computer Vision and Deep Reinforcement Learning algorithms to command the OPS-SAT reaction wheels in order to actively modify its attitude, so that the on-board optical camera keeps framed and focused on a target without the aid of any other instrument, such as the star tracker, the ADCS or the GPS receiver.



Adatica Engineering