Research Programs

Distributed FlatSat Phase 2

Digital Twin

This project aims to develop a distributed testbed for satellite testing, more commonly known as FlatSat integration testing. This phase of the project will develop node devices and a minimal software ecosystem that will enable geographically separated satellite hardware to undergo integration and hardware in the loop testing over the internet.

P2.53

Project Leader:
Dr Joon Wayn Cheong, Australia Center for Space Engineering Research (ACSER)

Participants:

SCARLET-β: Goal-Orientated Autonomy for Spacecraft

SCARLET Lab

The aim of this project is to research, develop and test goal-oriented algorithms and software that will grant a spacecraft autonomous capability to undertake its mission robustly and adaptively in real-time. The activities will focus on coupling optimisation and machine learning techniques to orbital and sensing prediction models, such that when sensing data is obtained in real time the next most optimal action can be determined.

The autonomy will be experimentally tested using the DSTG Buccaneer Main Mission (BMM) spacecraft scheduled to launch in 2023. BMM features the MANTIS payload with a controllable, deployable arm for self-inspection imaging. The project output will be a set of algorithms, methodologies, and approach to grant the spacecraft the ability to take an optimal image of itself against a backdrop of Australia in real-time. The outcomes will be learnings of the relationship between on-board and off-board autonomy that will be applicable to other spacecraft missions.

P2.54

Project Leader:
Professor Salah Sukkarieh, The University of Sydney

Participants:

Machine learning-enabled satellites for Agile Space Operations

On-board analytics

Space is becoming increasingly congested, contested, and competitive due to increased economic access to orbit, launches of distributed satellite systems, and conjunction events due to debris and conflict. For future satellite missions, on-board algorithms that can detect, track, identify, and characterise events and hazards that occur on-orbit will be required for space activities. One activity, autonomous maneuvering, is yet to be fully realised with the latest developments in artificial intelligence. Ability to test these
algorithms on the ground is limited and the capability does not exist in Australia. This project will commence with the development of a facility, and develop novel machine perception, navigation, guidance, and machine learning algorithms on space-based hardware.

P2.56s

Project Leader:
Dr Feras Dayoub, The University of Adelaide

PhD Student:
Harrison Bennett, The University of Adelaide

Participants:

Integrated Tactical Communications (ITC)

Dynamic Payloads – RF & Spectral

Secure, reliable, timely and resilient access to information is critical to success in any modern enterprise. This is especially true for military operations across the spectrum from humanitarian assistance and disaster relief (HADR) to battle in highly contested and congested environments.

Currently, the Australian Defence Force relies upon technology developed in the 1970’s to provide network connectivity for its arguably most at risk deployed forces. These systems have well known limitations yet there has been limited research into alternate technologies to support command and control and situational awareness for the tactical warfighter. The project seeks to identify and develop technology for advanced satellite communications as a long-term option to replace or augment these current high mobility satellite communications services.

The project builds on previous SmartSat funded research with a clear focus on three critical technologies to address this gap:

  1. Flexible and adaptive communications waveforms designed for the tactical user
  2. System wide network management to optimise resource allocation for capacity, coverage and resilience
  3. Reconfigurable, agile coverage using multi-frequency, multi-beam antenna arrays (pending future external funding)

This project will refine designs of the tactical communications waveform and initiate research into algorithms that optimise coverage and capacity of heterogeneous/hybrid satellite constellations including an initial demonstration implemented in software. The aim is to accelerate the technology development and understand risks in order to define a follow-on project, funded externally to SmartSat, that will develop a prototype space payload capable of integration with an experimental satellite. This subsequent phase will use the results from this project to inform the agile, multi-beam, multi-band phased array design and the development of initial user terminals. It is expected maturing this technology to the point it can be demonstrated in space will cost $5M – $10M and take three years. This is beyond the resource available from SmartSat so this project will include the
submission of a bid for Defence innovation/prototyping funding to support maturation of the critical underlying technology from TRL4/5 to TRL8.

The target technology demonstration and experimentation program for this research is the Defence STaR Shot for Resilient Multi-mission Space (RMS). The demonstration will showcase a game-changing approach to the provision of resilient satellite communications to the tactical warfighter.

Note: Within this project, tactical communications means systems supporting high levels of user mobility which requires the use of very small aperture terminals (e.g. handheld) and the ability to operate over complex RF propagation channels.

P1.30

Project Leader:
Jeff Kasparian, SmartSat CRC

Participants:

SatPing – a Tracking Beacon for Spacecraft

Debris Avoidance

Immense growth in the use of spacecraft and the orbital debris population is driving an urgent need for effective space traffic management (STM) and responsible use of space. Currently, orbital knowledge (position and velocity) is primarily obtained by ground-based remote sensing (e.g., radar, optical, etc.) which results in significant position and velocity uncertainty.

These uncertainties complicate conjunction assessments and subsequent collision avoidance manoeuvres.
The goal is to develop a self-sufficient, bolt-on system that can be used for active and real-time orbital knowledge (position and velocity) from the spacecraft.

A design approach to improve Space Traffic Management (STM):

  • Like an ADS-B for Spacecraft (analogous to air trafic management moving from radar to active GPS broadcast)
  • Chip continuously broadcasts a ‘ping’ to listeners
  • Determine position and velocity through RF geolocation (and/or GPS)
  • Low SWAP and no interface/interaction with spacecraft (‘bolt-on’)
  • Simple processor + Transmitter + Battery + Mini Solar array (+ GPS)
  • Provides information even for dead spacecraft or rocket bodies

We propose a short-term scoping study to evaluate the feasibility of this onboard beacon that can be used to provide high-precision, real-time orbital information – assessing ITU and RF broadcasting limitations, technical extent of existing capabilities and connecting with relevant Australian (and international) entities and regulatory bodies to advance the concept to implementation.

P2.50

Project Leader:
Associate Professor Shannon Ryan, Deakin University

Participants:

SCARLET-⍺: SpaceCraft Autonomy and Onboard AI for Next Generation Space Systems

SCARLET Lab

Spacecraft autonomy has been recognised as a key enabler of the next-generation space systems that aim at increasing responsiveness and continuity of space-based observations, covering large areas with higher resolutions, minimizing communication and data access latencies, and reducing costs of both the space and ground segments.

Spacecraft autonomy encompasses onboard autonomous decision-making capabilities that enable the space segment to continue mission operations and to survive critical situations without relying on ground segment intervention. It relates to all aspects of spacecraft operations, including continuous mission planning and execution on board, real-time spacecraft control outside ground contact, maximisation of mission objectives in relation to the available onboard resources and capabilities of other spacecraft, and system robustness in presence of on-board failures and external uncertainties.

This project aims at addressing the above requirements by developing novel concepts, methods and technologies to provide new AI-based spacecraft autonomy capabilities for the next-generation space systems, such as dynamically networked formations of heterogeneous satellites. It focuses on high impact areas of spacecraft autonomy and onboard AI as identified and prioritised with the industry and defence partners, including:

  • WP1: Onboard processing and actionable intelligence
  • WP2: Small spacecraft and constellation resilience
  • WP3: Dynamic optimisation of constellation resources
  • WP4: Real-time tasking and resource allocation

The output of this project is a set of autonomous algorithms, demonstrating their capability through software simulations with use-cases provided by the industry partners.

This project will leverage and contribute to the IPC Capability Demonstrator with an aim to be demonstrated on DST RMS STaR Shot as a pathway to commercialisation of the developed technology solutions for industry partners.

P2.52

Project Leader:
Professor Ryszard Kowalczyk, University of South Australia

Participants: