Research Programs

Ultra-fine Attitude Control via Event-based Star Tracking and Piezoelectric Stabilisation

Advanced Pointing

To fulfil mission objectives satisfactorily, many CubeSat-based applications require precise stabilisation of the CubeSat platform during orbit. For example, observing a small distant space object, (re)detecting small targets or fine-grain changes over a large terrain of the Earth’s surface, and establishing long-range communication links. However, in part due to their small size, CubeSats inevitably suffer from jitter during orbit, which prevents a high degree of stability.

This project seeks to research and develop an ultra-fine attitude determination and control system (ADACs) for optical remote sensing (Earth Observation and Space Situational Awareness) and optical communications from small satellite platforms.

P2.01

Project Leader:
Associate Professor Tat-Jun Chin, The University of Adelaide

Participants:

Trusted AI Frameworks for Change and Anomaly Detection in Observed ISR Patterns

On-board high-performance computing

This project seeks to automate the identification of higher order patterns in ISR (Intelligence, Surveillance and Reconnaissance) sensed detections along with establishing normalcy. The intention is for significant changes from normalcy – anomalies – to be reported to operators as alerts requiring human assessment, decision, and action. In addition, the rationale of the alerts will also be computed and presented in a transparent way to instil user confidence in the results.

Two novel aspects for this project are: (1) the use of multiple strategies for pattern detection, including deep learning and advanced statistical modelling (e.g., Bayesian Computation); and (2) the incorporation of a Pattern Question Answering (PQA) capability to enable intuitive interaction and interrogation of the reported patterns for their rationale. PQA will build on and generalise existing capabilities in Visual Question Answering (VQA) in the fields of Artificial Intelligence and Machine Learning.

Specific application domains will be considered to support the development and demonstration of capability, including domains such as maritime traffic, space situational patterns, and land use patterns.

P2.11

Project Leader:
Matthew Roughan, The University of Adelaide

Participants:

The Application of Artificial Intelligence for Satellite Enterprise Management

Agile & Self-healing systems

This project aims to focus on existing SATCOM enterprise architectures to quantify the performance gains achievable through the incorporation of Artificial Intelligence techniques.

P2.07

Project Leader:
Professor Jinho Choi, Deakin University

Participants:

Super resolution Mosaic Infrared Focal (SMIRF) Sensor

Infrared Sensors

When a satellite stops communicating it is difficult for an operator to determine the cause or nature of the failure and to determine an appropriate response.

Failures can be caused by many events including space based sub-system failures, impaired access to communication spectrum or spacecraft loss due to a collision with space debris. This project aims to advance the concept of a small, system independent suite of sensors and processors feeding information into an Artificial Intelligence (AI) based interpreter that will identify the potential jeopardy of the platform as well as propose an appropriate response.

This work is an important precursor to the development of cognitive satellites – satellites that are “context aware” of their operating environment and are able to independently self-configure to achieve increased mission resilience in a hazardous environment.

P2.22

Project Leader:
Mark Ramsey, SITAEL

Participants:

Space Jeopardy and Response (S-JAR)

Agile & Self-healing systems

When a satellite stops communicating it is difficult for an operator to determine the cause or nature of the failure and to determine an appropriate response.

Failures can be caused by many events including space based sub-system failures, impaired access to communication spectrum or spacecraft loss due to a<br>collision with space debris. This project aims to advance the concept of a small, system independent suite of sensors and processors feeding information into an Artificial Intelligence (AI) based interpreter that will identify the potential jeopardy of the platform as well as propose an appropriate response.

This work is an important precursor to the development of cognitive satellites – satellites that are “context aware” of their operating environment and are able to independently self-configure to achieve increased mission resilience in a hazardous environment.

P2.35

Project Leader:
Dr Hai-Tan Tran, Defence Science and Technology Group

Participants:

Measuring Control System Resilience to Cyber-Physical Threat in a Satellite Context

Trusted Autonomous Satellite Operations

Satellite infrastructure provides vital communications links for a number of critical industries, including; defence, transportation, utilities, oil and gas, emergency services, banking, environment, and others. It is therefore essential that such systems are protected from adversarial interference. Cybersecurity, in particular, has proven to be an immense challenge for satellite infrastructure, especially given the inaccessibility and long life-cycle of deployed space systems. Adding to the already complex security environment, satellite systems are evolving to include a vast array of new technologies, such as the Internet of Things (IoT), which introduces even more potential for vulnerabilities to be exploited by cyber adversaries.

Although there are many aspects to satellite protection that can and should be considered, this project addresses the specific issue of control system resilience to cyber-physical threat. Simply put, the project goal is to develop a satellite-centric resilience framework that considers all aspects of cybersecurity (i.e. technology, policy, and people), thereby supporting the generation of metrics to measure a satellite’s physical resilience (i.e. the ability to anticipate, withstand, survive, recover, and adapt) to cyber threats (i.e. nation states, terrorists, criminal groups, hacktivists, and individual hackers). With this framework satellite manufacturers and operators will be able to adequately assess their resilience posture in order to understand their risk exposure, and thus make any necessary changes to ensure they are protected against cyber actors wanting to maliciously degrade, deny, disrupt, or destroy their satellites.

P2.04s

Project Leader:
Dr Abdun Mahmood, La Trobe University, & Professor Jill Slay, University of South Australia

PhD Student:
Jordan Plotnek, La Trobe University

Participants: