SVP - Project proposals - DST · In order the ensure the continued airworthiness of military...

Contents AD SVP 01: Characterisation of trace oxygenated compounds in aviation fuels by application of

chemical derivatising reagents ............................................................................................................... 3

AD SVP 02: Air Operations Tactics Optimisation .................................................................................... 4

AD SVP 03: Alternative Methodologies for Aircraft Load Prediction ...................................................... 5

CEWD SVP 01: Laser Propagation Modelling ......................................................................................... 6

CEWD SVP 02: Cognitive RF EW Receiver Algorithm Development ....................................................... 7

CEWD SVP 03: Automatic Generation of Code Obfuscation Virtual Machines with LLVM .................... 8

CEWD SVP 04: Investigation of Network Control Protocol Vulnerabilities ............................................. 9

CEWD SVP 05: Bounded fault-tolerance in Autonomous Cyber Defence Systems .............................. 10

CEWD SVP 06: BLOS RF Propagation Studies ........................................................................................ 11

JOAD SVP 01: Air Operations Tactics Optimisation .............................................................................. 12

JOAD SVP 02: Developing an Information Management and Data-Mining Tool for Analysing Defence

Operations ............................................................................................................................................ 13

JOAD SVP 03: Air Operations Battlespace Visualisation ...................................................................... 14

JOAD SVP 04: Towards an Organisational Agility Maturity Model ....................................................... 15

JOAD SVP 05: Virtual Human Story-Tellers for Multimedia Narrative .................................................. 16

JOAD SVP 06: Neural Symbolic Cognitive Agent System (NSCAS) ........................................................ 18

JOAD SVP 07: Immersive Battlespace Demonstrator (ImBaD) ............................................................. 19

JOAD SVP 08: Immersive War gaming Tool Development ................................................................... 21

JOAD SVP 09: Prototype end-to-end Recommender System for Web-Based Geospatial Application . 22

JOAD SVP 10: Maritime Operational Availability Modelling ................................................................. 23

LD SVP 01: Vehicle Network Controlled PTZ Camera ........................................................................... 24

LD SVP 02: Distributed Decision Making Applications to support Autonomous Systems in Military

Land Vehicles ........................................................................................................................................ 25

LD SVP 03: Resilient Position Navigation and Timing for Ground Rovers ............................................. 26

LD SVP 04: Logistics World: Augmented Reality Reconfigurable Environment Visualisation Tool ...... 27

LD SVP 05: Collaborative Autonomous Vehicle Services; A Hybrid Control Approach ......................... 28

LD SVP 06: Collaborative Autonomous Vehicle Services; A Hybrid Control Approach (Different take on

project) .................................................................................................................................................. 29

LD SVP 07: Developing Methods for Measurements and Evaluation of Ground Truth Natural

Background Spectral 'Colors' using Hyperspectral Imagers .................................................................. 30

MD SVP 01: Neural Network Based Bathythermograph Data Verification .......................................... 31

MD SVP 02: Effect of Water Loading on the Frequency Response of a Simple Steel Cylinder ............. 32

MD SVP 03: Data Acquisition for a 60 Channel Towed Array ............................................................... 33

MD SVP 04: Acoustic Metamaterial One-Way Open Tunnel Concepts ................................................ 34

MD SVP 05: Clutter Mapping for Active Sonar Tracking ....................................................................... 35

MD SVP 06: Assessment of the Effect of Corrosion on Strength Properties of Ship Structures .......... 36

MD SVP 07: Calm Water Manoeuvring Performance of Naval Surface Vessels ................................... 37

NSID SVP 01: Passive Radar Calibration ................................................................................................ 38

NSID SVP 02: High Resolution Radar Imaging ....................................................................................... 39

NSID SVP 03: Small Satellite Ground Station Development ................................................................. 40

NSID SVP 04: Radar Detection In Sea Clutter ........................................................................................ 41

SES SVP 01: Materials characterisation of 3D Printed Plastics ............................................................. 42

SES SVP 02: Materials characterisation of 3D Printed Metals .............................................................. 43

WCSD SVP 01: Cooperative and Coordinated Strike with Multiple Networked Weapons ................... 44

WCSD SVP 02: Upgrade of Heat Treatment Furnace: PC Control ......................................................... 45

AD SVP 01: Characterisation of trace oxygenated compounds in

aviation fuels by application of chemical derivatising reagents

Location: Fishermans Bend, Victoria

Project Description:

Modern high performance aircraft fuel systems are operating at ever increasing temperatures,

placing extraordinary demand on fuels particularly when employed in a dual-use role cooling

hydraulic and avionics systems. This high thermal load induces oxidation of fuel, resulting in the

formation of oxygenated species which have been known to attack engine components and cause

failures and increased maintenance. A detailed understanding of aviation fuel oxidation chemistry is

crucial in formulating strategies to mitigate the detrimental effects of oxidised species, particularly

as the uptake of new of new alternate fuels increases. However, it is extremely difficult to

characterise oxidised compounds in fuels, which are only present in trace amounts, and are easily

swamped by the several hundred thousand hydrocarbons that make up typical aviation fuel. This

project aims to apply known derivatising reagents to thermally oxidised fuels to attempt to resolve

and detect trace oxygenated species containing particular functional groups, in order to more deeply

probe fuel oxidation chemistry.

Project Objectives:

1. Assess a set of derivatising reagents (such as dinitrophenylhydrazine, thiobarbituric acid,

diphenylpicryhydrazyl, ammonium cerium nitrate) for their applicability to the characterisation of

oxidised species in aviation fuel;

2. Determine optimum conditions for the aforementioned derivatising reagents to successfully react

with desired functional groups found in oxidised aviation fuels and implicated in poor fuel thermal

stability; and

3. Characterise chemically derivatives oxidised species to identify molecules which are likely to be

key contributors to the formation of detrimental solid deposits and poor fuel properties.

Project Activities:

1. Perform relevant wet chemistry laboratory and derivatising techniques;

2. Operate high performance liquid chromatograph (HPLC) and gas chromatograph (GC) instruments;

3. Basic analysis and interpretation of chromatograph data;

4. Apply derivatising reagents to thermally stressed conventional and alternate aviation fuels to

selectively target molecules with specific functional groups;

5. Characterise the derivatised components of oxidised fuels using high performance liquid

chromatography (HPLC) and gas chromatography (GC);

6. Prepare a written report detailing the project, methods and findings; and

7. Present a six minute 'pitch' presentation at the Defence Science Student Conference 2017.

Relevant Research Areas and Desirable Skills:

• Knowledge of aviation fuel oxidation chemistry

AD SVP 02: Air Operations Tactics Optimisation



This is a computer science research project exploring optimisation and (possibly machine learning

techniques) for finding optimal and robust values for artificial intelligence tactical behaviours in

simulation of air operation. Programming will be done in Python language.

Project Objectives:

1. Explore the effectiveness of a range of optimisation techniques and methods as applied to air

operations models.

Project Activities:

1. Problem definition and method selection;

2. Experimental design;

3. Implement the relevant experiments in Python;

4. Run experiments and produce results;

5. Analysis of results and prepare written report; and



• Computer Science experience in artificial intelligence, optimisation, machine learning or

simulation; and

• Python programming language, including scientific stack; NumPy, SciPy, Pandas, Jupyter.

AD SVP 03: Alternative Methodologies for Aircraft Load Prediction



In order the ensure the continued airworthiness of military aircraft it is necessary to understand the

physical forces (loads) which the aircraft are subject to in operational service. The precise

measurement of aircraft loading requires strain gauge instrumentation to be fitted and calibrated

through the application of known loads. During aircraft loading calibration activities, the loads

applied and resultant strain distribution in the structure is recorded. In subsequent analysis, DST

Group generally apply multi-linear regression methods to develop load equations which relate strain

to load. Whilst the standard analysis method is well understood, DST Group is interested in

determine if alternate mathematical analysis methodologies could be applied to this problem. Under

this project the student will be asked to research current and alternate analysis methods, undertake

data analysis of experimental data using different methods and comment on the validity and

advantages of new approaches.

Project Objectives:

1. Identification of mathematical analysis methods applicable to the prediction of aircraft loading

from ground load calibration data;

2. Investigation of alternate mathematical methods to determine validity and

advantages/disadvantages as compared to the standard analysis method; and

3. Reporting of results from investigation, including conclusions and recommendations for further

research

Project Activities:

1. Collation of relevant background material related to aircraft load calibration activities;

2. Research into current and alternative methodologies for analysis of load calibration data;

3. Selection of an appropriate alternate method(s);

4. Experimental data analysis, development of load equations and production of quality metrics;

5. Comparison of results from alternative method(s);

6. Reporting of results; and



• Statistical Analysis;

• Mathematical modelling and Optimisation;

• Static Load Analysis; and

• Physics.

CEWD SVP 01: Laser Propagation Modelling

Location: Edinburgh, South Australia


DST Group has developed a numerical model for simulating laser propagation through the

atmosphere. This has been applied to the characterisation of free space optical communications

systems. It is currently being transitioned to the CSIRO Bragg supercomputer, which will allow high

resolution modelling to be performed over long ranges, and include retro-reflector links. This

approach makes it feasible to study configurations which were previously impractical to do so.

We seek an SVP student to work under the guidance of our Research Scientists to apply this model

to a range of scenarios of significance to Defence applications.

Project Objectives:

1. Develop an understanding of laser atmospheric propagation and its effect on free space optical

communications;

2. Gain experience in numerical modelling and high speed computation; and

3. There may be the opportunity to participate in field measurements of the scenarios which have

been modelled.

Project Activities:

1. Undertake a background literature survey of atmospheric laser propagation modelling;

2. Become familiar with the DST Group model and its implementation;

3. In consultation with DST Group researchers, select one or two scenarios and undertake a detailed

modelling investigation of them;

4. Prepare a short written report on the project outcomes;

5. Present a 30 minute presentation on the project to CSS Branch; and


CEWD SVP 02: Cognitive RF EW Receiver Algorithm Development



Undertake the development of Machine Learning based algorithms for demonstrating the concept of

a Self-Learning Cognitive RF EW Receiver. The student will be asked to develop a computer based

prototype of a cognitive RF EW receiver processor using recommended Machine Learning algorithms

and system architecture. The performance of the prototype is to be tested using provided waveform

data.

Project Objectives:

1. Apply Machine Learning algorithms to the field of RF EW receiver processing;

2. Identify the capabilities and limitations of chosen Machine Learning algorithms; and

3. Demonstration of the concept of a Self-Learning Cognitive RF EW Receiver.

Project Activities:

1. Construct a computer based prototype of the receiver processor;

2. Train the Machine Learning algorithms using provided training data;

3. Assess the performance of the receiver processor using provided test data; and



• Knowledge of RF EW receiver processing

CEWD SVP 03: Automatic Generation of Code Obfuscation Virtual

Machines with LLVM



Code obfuscation virtual machines (such as VMProtect) embed the original program logic in a

custom bytecode that is subsequently executed by a custom virtual machine/interpreter. This makes

it incredibly difficult to recover the intent of the original program, because the analyst must first

reverse engineer the VM/interpreter before they can understand what the bytecode is doing. For

maximum effect, custom code obfuscation VMs can be developed for each program undergoing

protection. This development is typically done manually and in assembly.

The aim of this project is to automatically generate code obfuscation VMs in the LLVM pass

framework. While previous work has looked at extending LLVM with simpler program obfuscation

techniques, none have looked at the automatic generation of code obfuscation VMs in LLVM.

Project Objectives:

1. Develop an understanding of existing code obfuscation virtual machines;

2. Implement an obfuscation virtual machine generator in LLVM; and

3. Analyse the performance and effectiveness of the generated code obfuscation VM (e.g.

performance overhead, memory overhead, difficulty in reverse engineering etc.)

Project Activities:

1. Survey existing code obfuscation virtual machine technologies;

2. Develop a solid understanding of LLVM and developing LLVM passes;

3. Implement an obfuscation virtual machine generator in LLVM;

4. Evaluate the effectiveness of your obfuscation virtual machine generator; and

5. Present a six minute ' pitch' presentation to the Defence Science Student Conference 2017.

CEWD SVP 04: Investigation of Network Control Protocol

Vulnerabilities



There is an implicit reliance on telecommunication networks to keep us always connected. Research

over the past 20 years has demonstrated that attacks on network control plane protocols can have

significant consequences, including delays, eavesdropping, partitioning and black holing. Discovery

of routing protocol vulnerabilities is non-trivial; requiring a deep knowledge of protocol

specifications in order to understand their impact and develop mitigation strategies. The aim of this

project is to research one or more known routing protocol vulnerabilities in order to understand and

inform on its behaviour, the real world impact and consequences.

Project Objectives:

1. Under guidance, research a routing protocol vulnerability described in literature, implementing

code that can be used to analyse its behaviour; and

2. Characterise the behaviour and evaluate the real world impact of the vulnerability explored.

Project Activities:

1. Become familiar with the role that routers and routing protocols play in controlling how traffic

moves across a network. Focussing on a specified routing protocol, develop a deeper understanding

of its functions and how it operates to inform routing decisions;

2. Having been provided with a known routing protocol vulnerability, review the related literature;

3. Develop a methodology and design one or more experiments that can be used to explore and

evaluate the vulnerability;

4. Become familiar with a network emulation testbed and implement code to conduct repeatable

experiments to analyse the behaviour;

5. Compare and contrast findings with existing literature; explore and assess the real world impact of

the given vulnerability;

6. Produce a technical report that will summarise the routing protocol vulnerability studied from

literature, describe the approach taken for testing and evaluation including any assumptions made

and how data was collected, present the results and discuss the implications of the finding;

7. Periodically report on the above findings and provide a final presentation; and



• Telecommunications;

• Computer Networking;

• Electrical and Electronic Engineering;

• Computer Science;

• TCP / IP protocol suite;

• Software programming and scripting

languages (e.g. Python);

• Familiarity with Linux;

• Willing to learn new skills and tackle

complex problems; and

• Able to work independently;

CEWD SVP 05: Bounded fault-tolerance in Autonomous Cyber Defence

Systems



DST Group's Cyber Assurance and Operations Branch is undertaking ongoing research and

development in the area of autonomous cyber defence systems, which combine dynamic,

distributed security attack detection/response with vulnerability assessment and mitigation

Autonomous cyber defence systems are decentralised, meaning that they do not have a central

point of failure. Nevertheless, they are still susceptible to partial failures - for example, due to

network partitioning - which could interrupt the system's core defensive functions or reduce their

efficiency. In this summer project, the candidate will work as part of a team and will concentrate on

designing and implementing suitable algorithms for determining whether, and to what degree, an

autonomous cyber system can continue to function under partial failure, in the context of an existing

software prototype written in Golang (a programming language created by Google). In doing so the

student will be contributing to the distributed realisation of self-healing - an essential autonomic

self-property. No prior knowledge is expected beyond the completion of a 2nd year computing

curriculum that includes a course on data structures and algorithms, and ongoing coaching will

ensure that candidate is well supported. The work lies at the intersection of distributed systems and

autonomic/self-adaptive computing, and will equip the candidate with valuable knowledge and

software development experience on a real-life R&D project.

Project Objectives:

1. Acquire a basic understanding of fault-tolerance and self-healing in the context of autonomous

cyber defence systems; and

2. Undertake advanced software development with the aim of designing and implementing suitable

algorithms and attendant date structures for supporting self-healing in an existing prototype.

Project Activities:

1. Familiarisation with our development environment, tools and technologies (approximately 2-3

weeks);

2. Familiarisation with selected topics from autonomic computing (self-healing) and distributed

systems (approximately 1 week);

3. Designing and implementing suitable algorithms and data structures using Golang in the context

of an ongoing software prototype, contributing to the realisation of self-healing (approximately 7-8

weeks);

4. Preparing for and delivering a six minute ‘pitch’ presentation at the Defence Science Student

Conference 2017.

CEWD SVP 06: BLOS RF Propagation Studies



Propagation research remains a major component of the development of emerging radar and

communications systems at SSS Branch CEWD. The sea surface troposphere effects such as

absorption from atmospheric oxygen and water content, diffraction, refraction, ducting multipath

interference, earth-surface dielectrics and terrain interference play critical roles for RF radar and

communication systems. Anomalous Beyond-Line-of-Sight (BLOS) radio wav propagation at

microwave and mill metric waves (3-100 GHz) due to tropospheric scatter plays a major role in the

communication networking of data over large areas and in EW situational awareness. The student

will participate in a program of activity focused on ultimately providing improved propagation

modelling tools for assessing over the horizon propagation effects.

Project Objectives:

The RF Phenomenology and Susceptibility Section of RFT group in CEWD participates in trials

coordinating measurements of meteorological parameters, providing refractivity profiles in the

tropical sea surface environment and in the clear air mid-altitude troposphere, and RF network

reception measurements. The student will be tasked with an activity contributing to the analysis and

interpretation of these data sets. This would involve delivering outcomes in one of the following

areas of activity:

1. Data signal processing (the determination of RF system associated propagation factor and path

loss parameters in complex tropospheric environments);

2. Improving and validation of the parabolic equation based assessment tool currently used to model

the environmental impacts on RF systems, or; and

3. Validation of the meteorological numerical weather prediction models and in situ meteorological

measurements that provide the environmental inputs into the current assessment tools used to

interpret the RF reception measurements.

The outcomes of the project will be scoped according to the student’s skills set and interests.

Project Activities:

1. Advanced cross-spectral analysis using Fourier Transform based techniques that are MATLAB

based;

2. Improved parabolic equation modelling that involves the solving of the electromagnetic

propagation second order partial differential equation;

3. Design of a meteorological measurement system for coordinated RF reception studies; and

4. Present a six minute ‘pitch’ presentation at the Defence Science Student Conference 2017.

JOAD SVP 01: Air Operations Tactics Optimisation



This is a computer science research project exploring optimisation and (possibly machine learning

techniques) for finding optimal and robust values for artificial intelligence tactical behaviours in

simulation of air operation. Programming will be done in Python language.

Project Objectives:

1. Explore the effectiveness of a range of optimisation techniques and methods as applied to air

operations models

Project Activities:

1. Problem definition and method selection;

2. Experimental design;

3. Implement the relevant experiments in Python;

4. Run experiments and produce results;

5. Analysis of results and prepare written report; and



• Computer science student with experience in artificial intelligence;

• Optimisation;

• Machine learning or simulation;

• Python programming language; and

• Python scientific stack including; NumPy, SciPy, Pandas and Jupyter.

JOAD SVP 02: Developing an Information Management and Data-

Mining Tool for Analysing Defence Operations



1. Develop and deploy an information management portal for managing study and simulation results

using cutting-edge web technologies. Visualisation and filtering to focus on network graphs and

elastic lists; and

2. Explore methods for analysing big data by researching and employing novel techniques using data

analysis.

Project Objectives:

1. To create a capability where qualitative and quantitative data detailing Defence operations

research outcomes can be exploited most effectively for future reference.

Project Activities:

1. Data input and analytics are to be provided using a webpage frontend;

2. Information visualisation and rapid filtering are to be implemented using elastic lists;

3. Qualitative inter-relationships to be implemented using network graph theory; and

4. Present a six minute 'pitch' presentation to the Defence Science Student Conference 2017.

JOAD SVP 03: Air Operations Battlespace Visualisation



The successful applicant will have a Software Engineering / Computer Science background and will

develop an innovative system which will use augmented/ virtual reality to provide a unique view of

the battlespace to the user. The user will be able to see in three dimensions current and future Air

Force platforms conducting a mission while operating in a virtual environment. The system will be

based on commercial products, such as Oculus Rift or Microsoft HoloLens.

The system will allow multiple users to collaboratively construct new air combat scenarios. Users will

also have the ability to interact with the scenario as it is executing through gestures and voice

commands. The proposed system will be used by Air Operations Analysts and Air Force decision

makers, which will:

• simplify the process of defining complex joint scenarios;

• allow for a more natural and intuitive mechanism for interacting with visualisations of air

operations; and

• highlight the impact of decisions and effects.

The student will work within a small agile software development team.

Project Objectives:

1. Development of a prototype system capable of defining air combat scenarios through an

augmented/virtual user interface;

2. Include basic representations of Air Force platforms; and

3. Develop a system capable of user interaction through voice and gestures.

Project Activities:

1. Define scope and short requirements list;

2. Design a high level architecture for the proposed system;

3. Implement and test proposed system;

4. Report on findings; and



1. Software Engineering and/or Computer Science background;

2. Experience in Unity 3D games engine;

3. 3D graphics;

4. C Sharp;

5. Python; and

6. Javascript programming languages desirable.

JOAD SVP 04: Towards an Organisational Agility Maturity Model



While the importance of agility has long been recognised by Defence, there is no universal

agreement (in Defence or in the broader scientific literature) on the exact definition of the term, or

how agility may be assessed and improved. This study aims to contribute to the development of an

organisational agility maturity model, a methodology and a best-practice benchmarking tool for

evaluating organisational agility and developing relevant improvement strategies. The study may

deal with any of the following aspects in relation to organisational agility: organisational learning,

knowledge management, strategic management, research and development, governance, culture,

change management, decision making, leadership, risk management etc.

Project Objectives:

1. Targeted literature review;

2. Conceptual framework; and

3. Draft journal paper.

Project Activities:

1. Conduct a targeted literature review on one of the relevant aspects (maturity indicators) as

outlined project description;

2. Integrate the literature review into a conceptual framework;

3. Relate the conceptual framework to other maturity indicators (preliminary maturity model);

4. Contribute to a journal paper on the topic; and


JOAD SVP 05: Virtual Human Story-Tellers for Multimedia Narrative



The Defence Science and Technology group has an active research program into the use of

multimedia narrative to provide situational awareness for military C2. As part of this research DST

Group has developed interactive Virtual Humans dubbed Virtual Advisors. Virtual Advisors are

computer generated humans that combine photo realistic textures with real-time 3D animation and

speech generation to provide an on-demand, natural Human-Computer Interface. DST Group's

Project Team is exploring how autonomous AI and trusted interfaces can be used to support military

operations and intelligence analysis, in collaboration with international partners. The development

of an interactive multimedia storytelling capability to provide situational awareness, leveraging

existing in-house capabilities, is a key element to achieving a trusted interface to autonomous

systems in these use cases.

Situational awareness is a key requirement for decision makers and analyst. In the normal course of

their roles this is achieved, in part, by exploration and manipulation of the data space in order to

produce the products needed to support their analysis and decisions. This helps establish the

context, and determine what is known, what is not known, and what is important and what is not

important to a particular situation. When automation is introduced to handle large data sets, this

pathway to situational awareness is largely lost. However, storytelling is widely regarded as an

effective mechanism for experientially engaging an audience, and thus can establish the context

needed to achieve situational awareness in these circumstances. Beyond this, narration associated

with multimedia content can help explain a graphic, animation, or scene, and point out the

significance of what is being displayed. Therefore, we have been exploring the use of automated

multimedia narrative, based around animated virtual human characters coupled with text, images,

videos, graphs, diagrams, 2D/3D animations and geospatial scenes, as a means of providing users

with the elements needed to achieve situational awareness when automation is used for data

analysis and fusion. In particular, interactive virtual humans have the potential to provide an

engaging narrative that goes beyond a simple 'voice-over', through the display of appropriate

emotions and the use of appropriate gestures. Modelling of the user's cognitive and emotional state,

and that of the virtual human 'storytellers', are important to achieving this engagement. With the

increasing shift towards autonomous systems with 'humans on the loop' rather than 'humans in the

loop', there will be an increasing need for such engaging interfaces.

In this project the student will extend a prototype version of the Virtual Adviser system

implemented using the Unreal Engine game engine. This project work will develop photorealistic

engaging characters, and multimedia interfaces, to improve user immersion in a multimedia

narrative. Some of this work may include integration of new technologies into the rendering engine.

Project Objectives:

1. Extend the character animation capabilities of the rendering engine to support higher fidelity,

articulated body models and associated rigging; and

2. Develop and/or extend the set of complimentary multimedia rendering capabilities.

Over page

Project Activities:

1. Software is developed following current established best practices such as the use of an agile

development methodology and Continuous Integration;

2. All source code is appropriately commented and checked into DST Group's code repository;

3. Working software is deployed on the Research Network;

4. All supporting configuration instructions, operating instructions and lessons-learned

documentation are provided in an agreed format; and

5. Present a six minute 'pitch' presentation at the Defence Science Student Conference 2017;


• Interactive Virtual Humans;

• Multimedia;

• Computer Science;

• Java Programming;

• C++ Programming;

• 3D Computer Graphics;

• 3D Game Engines; and

• Software Engineering.

JOAD SVP 06: Neural Symbolic Cognitive Agent System (NSCAS)



The successful applicant will be working in a small team of researchers and developers, learning

cutting edge machine learning techniques and building a cognitive agent system in which the agent

is capable of learning from experience and reasoning about what has been learnt in a

computationally efficient way. Many such agent systems use either statistical type approaches or

symbolic (e.g. rule-based) approaches. Since it is desirable to be able to integrate both types of

approaches to get the best of both worlds and to have the agent be able to update itself as its

experience grows and its knowledge changes, the agent system for this project will be developed

according to a framework known as the Neural Symbolic Cognitive Agent Systems (NSCAS)

framework because it supports both of these aims.

Project Objectives:

The broad objective of the project from DST Group perspective is to develop a prototype capability

which may be employed for developing trusted autonomous systems.

However, from the perspective of the actual work to be conducted, the overall objective of the

project is to implement and demonstrate part of a NSCAS agent system. Briefly, NSCAS agent

systems comprise three components for learning, reasoning and explanation. This project will focus

on the learning and reasoning components. Then learning component consists of a set of rules to

represent the agent's background knowledge and examples which represent the agent's experience.

The rules are then translated systematically into an equivalent artificial neural network which is

trained by the reasoning component using the examples and is ultimately used for conducting

reasoning. As new examples or rules become available, the process can be repeated to update the

agent's knowledge. In terms of this description, the more specific objectives of this project are:

i) Implement the translator that converts the rules into a neural network;

ii) Use existing software libraries to train and reason with the neural network; and

iii) Demonstrate the system by learning rules of robotic soccer from Robocup data.

Project Activities:

The student will have the opportunity to work on all facets of software development. It is not

expected that the student will have experience in all of these areas. Tasks may include:

1. Briefly learning about rule-based systems and neural networks;

2. Investigating and choosing an appropriate deep learning (neural network) library in Java and

Python;

3. Setting up the software development environment;

4. Implementing the translator based on the chosen library;

5. Running tests against the social Robocup data for learning rules of robotic soccer; and

6. Presenting a six minute 'pitch' presentation at the Defence Science Student Conference 2017.

JOAD SVP 07: Immersive Battlespace Demonstrator (ImBaD)

Location: Eveleigh, New South Wales


This project is to develop a first person virtual reality battlespace exploration tool using the Unreal

game engine for use in exploring future war fighting concepts for the Australian Defence Force

(ADF).

The ImBaD tool is a first person sandbox simulation in which the user can wander around a theatre

of operations at the scale of a titan and shrink down at will to explore in more detail.

It is primarily intended to demonstrate new technology concepts of relevance to Joint Fires in the

exploratory force (the Australian Defence Force as it might look sometime in the 2035 to 2050

timeframe).

The tool utilises a VR headset such as the Oculus Rift and incorporates inputs from devices such as a

Virtuix Omni for moving around the theatre and tools such as Leap Motion or Sixense Stem for VR

object manipulation and selection.

Project Objectives:

The ImBaD tool development will have started before this project commences and some of the

objectives of this project may already have been completed. In consequence, a longer list of

objectives has been provided that is feasible for the student to complete. The specific objectives for

this project will be determined in the light of the current state of development and the student’s

capabilities.

1. The primary purpose of ImBaD is to facilitate the exposure of Joint Fires subject matter experts to

the types of technology concepts which may be relevant in the exploratory force. One objective is

developing a (loosely) specified new technology concept for use in ImBaD (e.g. semi-autonomous

swarm strike capabilities)

2. Theatres of operation potentially include multiple countries and need to be largely generated

from real world elevation data, satellite imagery and mapping information. One objective is

developing an automated pipeline to facilitate building some aspects of the VR model of the theatre

of operations inside ImBaD.

3. Include a range of overlays which permit the operator to see different aspects of the

environment. E.g. satellite imagery, troop dispositions, mission objectives, target lists. One objective

is developing an overlay to support a specific set of operator needs.

4. Unreal engine will shortly include a capability to Build VR in VR. One objective is to use the

concept and source code for this to provide the mechanisms for ‘theatre decorators’ to work inside

the VR environment to place friendly, enemy and neutral assets (e.g. tanks), vegetation and

buildings.

Over page

Project Activities:

1. Understand existing ImBaD capability including its roles, functionality, design and implementation.

(Week 1);

2. Understand the proposed enhancements to ImBaD including their functionality and roles and

develop a high level design and implementation plan for the proposed enhancements. (Week 2);

3. Using an agile development approach, in three three-week sprints:

i. Design, implement, test and demonstrate the required enhancements

ii. Use a wiki to document the methodology and algorithm used to build the tool

iii. Write in-game user guidance and video instructions for the enhancements

iv. Present and demonstrate the enhancements to JSEW staff (weeks 3 to 11);

4. Present and demonstrate the enhancements made to the ImBaD tool to SMEs from the joint fires

study working group (Week 12); and

5. Present a six minute ‘pitch’ presentation at the Defence Science Student Conference 2017 (Week

12).

JOAD SVP 08: Immersive War gaming Tool Development



This project is to develop an immersive war gaming tool using game engines for Joint Fires Table Top

Exercises (TTX).

Project Objectives:

1. Using COTS game engines tool to develop a turn based strategy (TBS) tool for joint fires TTX;

2. Develop a Scheme of Manoeuvre (SoM) for each turn; and

3. Develop a combat adjudication tool.

Project Activities:

1. Demonstrate the TBS tool to joint fires study working group;

2. Document the methodology and algorithm used to build the tool;

3. Write a user manual for the use of the tool; and


JOAD SVP 09: Prototype end-to-end Recommender System for Web-

Based Geospatial Application



DST Group's Project SAKI Geo is a web-based geospatial search and planning tool aimed at providing

situational awareness to enable better time critical decision making for military operations. With

more and more information being added to the system, the users will need a mechanism to have

targeted content delivered to them. A knowledge-based recommender system has been proposed

for use in SAKI Geo. The system will learn from these interactions to deliver targeted content to the

users.

The student project will prototype end-to-end knowledge-based recommender system. The system

will inspect user preferences, search and navigation logs to identify patterns within the usage of SAKI

Geo. This may include integration of new technologies into SAKI Geo.

SAKI Geo utilises the latest web technologies and tools such as AngularJS, Leaflet, Node.js, MongoDB

and RESTful services. It is proposed that the system would be developed using various JavaScript

frameworks to leverage existing in-house software and new technologies. The successful candidate

would be part of the SAKI Geo team who develop software under a continuous integration

environment (JIRA, Jenkins, Stash, Git) and apply agile practices to software development. This is a

great opportunity to gain experience, learn and work within a software development team

developing web applications.

Project Objectives:

1. Prototype end-to-end knowledge-based recommender system to improve search, navigation and

content presentation;

2. Defined use cases, as part of the development of the user interface components; and

3. Prepare and conduct internal demonstrations.

Project Activities:

1. Prototype a knowledge-based recommender system that utilises user preferences, search and

navigation logs to identify patterns within the usage of SAKI Geo;

2. Prototype user interface concepts using the recommender system to improve search, navigation

and content presentation;

3. Perform configuration management using GIT and participate as a SAKI Geo Team member;

4. Final placement presentation; and



• Web application development (JavaScript programming);

• Software engineering.

JOAD SVP 10: Maritime Operational Availability Modelling

Location: Eveleigh, New South Wales


The project involved software re-engineering and documentation of existing JAVA simulation

software that models Maritime Patrol Operations. The finished package should be extensible, and

written in the Python programming language.

The project would encompass review of existing simulation models with view to extending modelling

capabilities; software design and implementation, VVA and testing of code and documentation of

the developed system.

Project Objectives:

1. To modernise existing Monte Carlo simulation software and make it amenable to future extension

and development.

Project Activities:

1. Review existing programming models;

2. Undertake software requirements and specification;

3. Architectural and object design;

4. Programming implementation (in Python), documentation and testing; and


LD SVP 01: Vehicle Network Controlled PTZ Camera



The Advanced Vehicle System team is developing an automatic management system for vehicle

digital systems. This student project will develop a software interface between a Pan Tilt Zoom (PTZ)

camera and the management system based on the Generic Vehicle Architecture (GVA) a vehicle

systems standard architecture.

Project Objectives:

1. A software interface that allows the camera to be controlled over an intra-vehicle network.

Project Activities:

1. Document how the PTZ camera works;

2. Create a software interface (touchpoint) that allows the PTZ camera to be controlled and to

stream video over a GPA network, this software should be written with re-use in mind. There should

be minimal effort required for it to be used with a different camera;

3. Document how all developed software works, its applicability, the assumptions made in

development and constraints;

4. Document how the software could be used to interface with a different device; and


LD SVP 02: Distributed Decision Making Applications to support

Autonomous Systems in Military Land Vehicles



The research program of the Advanced Vehicle Systems (AVS) group seek to identify opportunities

and develop novel solutions to enhance the adaptability, tactical effects and resilience of critical

services on Army's future land vehicles. This may be achieved through exploitation of redundant

functionality afforded by distributed digital vehicle systems and utilisation of sensors and effectors

on co-located vehicles in the land battlespace. To realise these capabilities, the AVS group is

investigating the use of automatic management of vehicle systems and distributed decision making

concepts.

The student will focus on research into distributed decision making methods and tools to support

autonomic self-management of services within military land vehicles. Previous research in this space

has identified a collection of useful methods for distributed decision making. This project will

research their validity and implementation in systems and scenarios of interest to AVS.

Project Objectives:

1. Understand and document the performance, requirements, constraints and trade-offs of specific

distributed decision making methods in use cases within the AVS research scope; and

2. Provide recommendation as to tools for modelling and simulation of distributed decision making

methods.

Project Activities:

1. Familiarise with AVS research into distributed decision making methods;

2. Develop simulations to provide concept demonstration of relevant distributed decision making

methods;

3. Develop simulations to analyse the implementation and fitness of methods for distributed

decision making between systems of interest in representative AVS scenarios;

4. Report on distributed decision making methods and associated analyse highlighting performance,

requirements, constraints and trade-offs; and


LD SVP 03: Resilient Position Navigation and Timing for Ground

Rovers



The Advanced Vehicle Systems team is developing an Autonomic Management System for vehicle

digital systems. Army vehicles require resilient positioning services in order to operate in current and

future environments. Satellite based navigation systems (GNSS) are not always available and few

vehicles are equipped with GNSS independent inertial navigation systems. This project looks to

explore resilient positioning of ground rovers (robots) using GPS, inertial systems, and observation of

landmarks and other friendly ground rovers while exchanging data over an inter-vehicle network.

Project Objectives:

1. Understand the performance capabilities of the different position sensors;

2. Make technical recommendations for future sensors based on cost and performance; and

3. Make architectural recommendations for the integration options for the position based sensors.

Project Activities:

1. Integrate position sensors with the robot control system;

2. Assess the performance of different position sensors for robot position, control and guidance;

3. Develop software interface that allows the positions sensor to operate with the position service of

the vehicle Autonomic Management System;

4. Integrate position sensors with the position service of the vehicle Automatic Management

System;

5. Assess the performance of the position service of the vehicle Automatic Management System

using precise robot position as a reference; and


LD SVP 04: Logistics World: Augmented Reality Reconfigurable

Environment Visualisation Tool



The Land Logistics group is looking to develop the concept of a reconfigurable environment/terrain

visualisation tool that is part physical, part virtual - using Augmented Reality (AR). The intention is for

such a tool to allow the exploration visualisation and demonstration of concepts in the Land Logistics

area (initially) as well as for enhancing communication and engagement with stakeholders. This

project contributes to the development of the 'virtual' part through implementing an AR interface

that can determine physical object location, orientation and identification, and can visualise virtual

objects in conjunction with physical ones.

Project Objectives:

1. Articulation of technology requirements and design considerations;

2. Preliminary implementation and demonstration of the AR system components; and

3. A basis for the continued development, implementation and enhancement of the Augmented

Reality Visualisation tool.

Project Activities:

1. Investigate suitable AR hardware and software;

2. Implement physical ‘play space’ location and orientation within the AR interface;

3. Implement graphical and textual information overlay within the AR interface;

4. Implement the visualisation of virtual objects within the AR interface;

5. Documentation of the above; and


LD SVP 05: Collaborative Autonomous Vehicle Services; A Hybrid

Control Approach



The research program of the Advanced Vehicle Systems (AVS) group seeks to identify opportunities

and develop solutions to improve the resilience and adaptability of critical services on Army's future

land vehicles. Modern land vehicles capabilities require increased agility in configuration,

deployment and self-management of vehicle-hosted sensors and effectors.

In regard to controlling these systems, almost all operational systems are composed of both physical

components that operate in continuous-time as well as cyber control, sensing and communication

systems that live on embedded circuits and operate in discrete-event time. Hybrid control is a

modern control theory that addresses both the physical and the cyber parts of a system and their

difference in time scales. Hybrid control has proven advantageous in systems involving groups of

complex systems, sequential planning of complex autonomous behaviours and rigorous modelling of

embedded control systems. This project involves research on cyber-physical systems, familiarisation

with hybrid modelling tools, concept design and demonstration of hybrid control in a collaborative

fleet of autonomous vehicles.

Project Objectives:

1. Brief familiarisation with hybrid control methods (Reference book: Introduction to Embedded

Systems, A Cyber-Physical Systems Approach. Lee and Seshia 2015) relevant to the collaborative

vehicles program of AVS;

2. Familiarisation with existing hybrid modelling tools either in Simulink or LabVIEW; and

3. Design and concept demonstration of a collaborative autonomous behaviour in a group of vehicle

systems.

Project Activities:

1. Document a report on hybrid control and the associated analysis of the collaborative autonomous

behaviour of the multi vehicle system;

2. Simulate and demonstrate the utility of the concept algorithms; and


LD SVP 06: Collaborative Autonomous Vehicle Services; A Hybrid

Control Approach (Different take on project)



The Advanced Vehicle Systems (AVS) Science and Technology Capability (STC) provides support to

Army and the broader Defence community on issues and opportunities of adopting and integrating

advanced technology capabilities into Land Vehicles. Two characteristics of common challenges in

land vehicles are:

1. Vehicles are never alone, and

2. Individual vehicles rarely have sufficient capabilities for the most challenging situations.

Hence, cooperative resource management and collaborative tasks are necessary.

The students’ involvement will focus on research into distributed machine learning in collaborative

resource allocation.

Project Objectives:

1. Identify and evaluate a range of machine learning methods for the resource allocation task;

2. Understand and document the performance, requirements, constraints and trade-offs of machine

learning framework for distributed resource allocation within the AVS simulation environment; and

3. Make recommendations for future work in this area.

Project Activities:

1. Demonstrate machine learning for the purpose of resource allocation within AVS’s wargame

simulation environment;

2. Advise on strengths, weaknesses, and future directions for work in this area in consultation with

AVS researchers; and


LD SVP 07: Developing Methods for Measurements and Evaluation of

Ground Truth Natural Background Spectral 'Colors' using

Hyperspectral Imagers



Hyper Spectral Imaging (HS I) is a recent sensor technology that has become more readily available

and accessible. However, there is a lack of knowledge and understanding of the electromagnetic

spectral characteristics of terrain backgrounds, vulnerability of Army assets and potential

development of countermeasures against these new HSI technologies.

This project will require the student to learn to operate newly acquired hyper spectral imagers (400-

1000nm, and 900-1700nm) and to use relevant analytical software tools for hyper spectral data

analysis.

The aims of this study are:

1. To develop a measurement procedure for ground base HSI field data collection including

calibration and meta data format; and

2. To investigate image processing techniques to extract 'spectral colours' and spatial frequency

contents of different backgrounds for vulnerability assessment and countermeasure development

i.e. camouflage pattern design.

Project Objectives:

1. Develop a Standard Operating Procedure (SOP) for ground base HSI data collection; and

2. Develop appropriate techniques for characterisation and classification of spectral reflectance and

spatial frequency between backgrounds and man-made targets.

Project Activities:

1. Carry out an appropriate field trial that collects high quality relevant image imagery;

2. Generate a database with appropriate metadata and documentation of the imagery set collected

and with practical and well-documented procedures for access to the data;

3. Conduct imaging analysis and investigate imaging processing techniques in characterisation and

classification of the data cube to exploit difference in spectral and spatial characterisations to

discriminate features between natural background elements and man-made targets; and


MD SVP 01: Neural Network Based Bathythermograph Data

Verification



Expendable Bathythermographs (XBT) are routinely deployed by Navy to measure water

temperature versus depth. Water temperature affects sound velocity, which is key to understanding

acoustic propagation in the ocean. XBT data is prone to corruption from a number of phenomena.

This project seeks to develop a Neural Network or Expert System based system to detect when XBT

data is corrupted.

Project Objectives:

1. Produce a database for Neural Network or Expert System training for existing XBT data;

2. Develop and train a Neural Network or Expert System to classify good / bad data; and

3. Demonstrate the system.

Project Activities:

1. Curate and aggregate existing XBT data into a database;

2. Prototype and test algorithms in MatLAB;

3. Implement and test algorithms in C++;

4. Produce a report; and


MD SVP 02: Effect of Water Loading on the Frequency Response of a

Simple Steel Cylinder

Location: Stirling, Western Australia


The successful candidate will be required to participate in current research being performed at DST

Group and the University of Western Australia on near field acoustics. This project will focus on

measuring the effects of water loading on the frequency response of a simple cylinder and

investigating the effects of water depth on this response. Measurements will be done in the

laboratory and at the open ocean Magnetic Treatment Facility on Garden Island. Provided there is

time results will be compared to theoretical results obtained using a finite element model such as

ANSIS or ABACUS.

Project Objectives:

1. Measure the effect of water loading on the frequency response of a simple cylinder;

2. Map model shape changes with water depth; and

3. Compare results to computational models (provided 1 and 2 have been completed).

Project Activities:

1. Experimental vibration analysis;

2. Model analysis;

3. Computation modelling; and


MD SVP 03: Data Acquisition for a 60 Channel Towed Array

Location: Stirling, Western Australia


The successful candidate will be required to write software using LabView to collect data from a 60

hydrophone array currently installed on the research vessel Whale Song. This array will be used to

track marine mammals and assist the Royal Australian Navy in various operations. The student will

be required to work closely with researchers at Curtin University and DST Group with the possibility

of participating on a trial on Whale Song to test the final system.

Project Objectives:

1. Develop a simultaneous 60 channel acquisition system in LabView; and

2. Participate in testing of A/D system in laboratory.

Project Activities:

1. LabView programming;

2. Become proficient in digital signal conditioning and processing; and


MD SVP 04: Acoustic Metamaterial One-Way Open Tunnel Concepts



Acoustic metamaterials are artificial structures made of sub wavelength units such that their

acoustic properties are tailored to produce new behaviour not possible with conventional materials.

One aspect that has attracted research interest is the application of acoustic metasurfaces to control

acoustic waves in a channel. An example being an Acoustic One-way Open Tunnel (AOOT).

The aim of the project is to review proposed design concepts for AOOTs, choose a concept and

create a CAD design. Then computer aided manufacture options will be assessed including 3D

printing and routing. Suitable base materials will be chosen. The design will then be made and an

experimental test plan developed and undertaken to measure the performance. Assistance will be

provided at the various stages.

Project Objectives:

1. Generate a design of a one-way acoustic tunnel using acoustic metasurfaces;

2. Fabricate the design using computer aided manufacture; and

3. Develop test and undertake test method to measure the performance of the design.

Project Activities:

1. Conduct a focused literature on acoustic metasurfaces and metamaterials for one-way tunnels;

2. Introduction to CAD software and generate concept designs;

3. Review suitable materials and manufacturing methods;

4. Develop experimental test plan including measurement approach;

5. Manufacture components of design for testing;

6. Undertake measurements;

7. Collate results and write report; and


MD SVP 05: Clutter Mapping for Active Sonar Tracking



The tracking and classification of underwater targets using active sonar is a challenging problem due

to the highly variable nature of the underwater environment. Persistent clutter returns from marine

life, the sea surface and sea floor can make It difficult to track underwater targets of interest.

For some problems, it is common to assume that the distribution of the clutter and background

noise is uniform or known. However in active sonar, the clutter is non-uniform in shape and

intensity, and also evolves with time. In this project, the student will develop clutter mapping

models for active sonar that estimate the size, shape and intensity of clutter returns. This model will

be used in conjunction with filtering algorithms to help distinguish true target returns from clutter.

In particular, the student will consider the application of Markov Random Fields to the active sonar

clutter mapping problem and compare its performance with existing methods using simulated data.

Project Objectives:

1. Clutter map model implementation used in conjunction with existing tracking algorithms; and

2. Initial investigation into the performance of tracking algorithms with and without clutter map

model.

Project Activities:

1. Work with DST Group supervisor to implement a Markov Random Field clutter model to a

simulated high clutter scenario in MATLAB;

2. Work with DST Group supervisor to integrate the clutter model into existing tracking algorithms;

3. Perform simulations to compare the performance of the Markov Random Field clutter model with

existing methods in the context of Kalman filtering and Probabilistic Data association;

4. Work with DST Group supervisor to document clutter model and simulation results; and


MD SVP 06: Assessment of the Effect of Corrosion on Strength

Properties of Ship Structures



The structural assessment of degraded naval structures is paramount in determining life of a

structure and its extension. The project will investigate the effect of corrosion on structural integrity

of a naval surface ship. Specifically, this project will utilise finite element modelling within the

COMSOL Multiphysics modelling package to model the change in strength properties of a selected

cut down ship structure such as a stiffened plate when corrosion has occurred. The model will

investigate pitting corrosion at varying locations on the stiffened plate, with varying pit densities and

varying depths.

Project Objectives:

1. Establish a computer model of the selected cut down ship structure;

2. Establish a process for modelling corrosion within the ship structure; and

3. Assess the effect of likely corrosion on structural strength properties of the ship structure.

Project Activities:

1. Conduct a literature review on the effects of corrosion in naval structures;

2. Introduction and learning of COMSOL Multiphysics software package;

3. Build a model within COMSOL of a cut down ship structure such as a stiffened plate;

4. Analyse the strength properties of the model;

5. Incorporate corrosion into the model and analyse the effect of corrosion on the established

strength properties;

6. Final report on effect of corrosion on strength properties of ship structure; and


MD SVP 07: Calm Water Manoeuvring Performance of Naval Surface

Vessels



This project will involve the development of analysis and visualisation routines for characterising the

calm water manoeuvring performance of naval surface vessels.

General Requirements

• Strong written and oral communication skills are essential, as is the ability to work as part of

a team.

• High levels of initiative and self-motivation are required, including the ability to work

independently in unsupervised environments.

• Experience with desktop applications such as Word, Excel and PowerPoint is essential.

• Demonstrated programming experience in MATLAB is essential.

Other Desirable Skills

An understanding of hydrodynamics, manoeuvring, seakeeping and naval architecture concepts

would be advantageous.

Project Objectives:

1. Develop MATLAB-based software for analysing ship motion & manoeuvring performance

2. Develop MATLAB-based software for visualising manoeuvring performance results

3. Apply analysis & visualisation software to full-scale ship trial data

Project Activities:

1. Prepare raw full-scale trial data for post-processing.

2. Develop numerical routines for analysing ship motion & manoeuvring performance.

3. Develop graphical tools for visualising manoeuvring performance results.

4. Apply analysis & visualisation routines to full-scale ship trial data

5. Integrate newly developed capabilities into existing software suite.

6. Produce a report detailing work carried out and main findings.

7. Present a 6 minute “pitch” presentation at the Defence Science Student Conference 2017.

NSID SVP 01: Passive Radar Calibration



DST Group's Passive Radar Demonstration system uses arrays of antennas and receivers to provide a

360 degree persistent surveillance capability, using illuminators of opportunity in the environment.

Researching existing techniques, devise a method for calibrating a ring of antennas installed in a

passive radar system, to improve the angle estimation of the passive radar when detecting aircraft.

Project Objectives:

1. Improve angle estimation for passive radar system when using ring array of antennas.

Project Activities:

1. Research calibration techniques;

2. Undertake field experiments to collect data using the passive radar system;

3. Using MatLab, apply the calibration to improve the detection of aircraft using the passive radar;

4. Write a report on the results of the calibration experiments; and


NSID SVP 02: High Resolution Radar Imaging



The project is in the area of signal processing - you do not need to know anything about radars when

you start.

You will be working with a small, dedicated group of researchers to improve the resolution and

image quality of imaging radars so as to improve the classification of difficult-to-classify long-rang

targets.

The project focus: advanced application of the keystone transform for range-walk correction due to

target rotational motion.

Project Objectives:

1. Determine the bound of rotational motion for which the keystone transform correction for effects

from first-order terms is sufficient;

2. Design the rotational motion compensation algorithm based on the keystone transform correcting

also for the second-order term; and

3. Apply the algorithm to simulated data of simple rotating objects.

Project Activities:

1. Learn the theoretical background of the keystone transform;

2. Learn the existing MatLab implementation of the keystone transform for the first-order term

effects of rotational motion;

3. Investigate and implement the extension of the keystone transform to correct for effects from the

second-order term;

4. Characterise its performance versus coherent processing time and noise;

5. Contribute to the writing of a DST Group Technical Report; and


NSID SVP 03: Small Satellite Ground Station Development



The NSID small satellite team is developing a ground station to support the Buccaneer CubeSat

missions. This project has a software engineering focus and will involve the development of new

features for the mission control software that will be used to communicate with the satellite and

plan future missions.

Project Objectives:

1. Improve the usability of the ground station mission control software;

2. Gain experience in software design and development in an agile environment; and

3. Gain experience in controlling a satellite and mission operations.

Project Activities:

1. Liaise with ground station operators to identify new features or areas of improvement in the

mission control software;

2. Implement new features and bug fixes to improve the functionality of the mission control

software;

3. With guidance from ground station operators, plan a satellite mission and command the satellite;

and


NSID SVP 04: Radar Detection In Sea Clutter



Analysis of real sea clutter will be used to determine a model for its statistical nature. This will then

be used to produce a detector which will be run on it.

Project Objectives:

1. Contribute to mathematical model;

2. Develop radar detection scheme; and

3. Implement and test the model and scheme.

Project Activities:

1. Work collaboratively with supervisor;

2. Contribute to modelling;

3. Contribute to report on the work conducted; and


SES SVP 01: Materials characterisation of 3D Printed Plastics



Undertake materials characterisation activities on various 3D printed plastics. The project will

require the student to design and familiarise themselves with the manufacture of test specimens,

and additionally design and conduct mechanical testing on the specimens. Specific unique designs

will also be nominated to the student for investigation. The student will be required to have a solid

understanding of materials and finite element software, and compare the analytical and test results.

The testing will need to consider various factors controllable in the additive manufacturing process

such as build speed, part orientation, support type and part design.

Project Objectives:

1. Document the mechanical properties of 3D printed plastics taking into account factors

controllable in the additive manufacturing process

2. Investigate the mechanical strength of various unique designs and compare the

analytical and test results

Project Activities:

1. Develop a test plan for mechanical characterisation of 3D printed plastics taking into account

factors controllable in the additive manufacturing process

2. Undertake mechanical testing to determine mechanical characteristics of 3D printed plastics.

3. Undertake structural analysis and mechanical testing of various unique designs, and

compare the results.

4. Document all activities conducted in a project report

5. Present a 6 minute ‘pitch’ presentation at the Defence Science Student Conference 2017 and

to relevant engineers or researchers within DST Group.

SES SVP 02: Materials characterisation of 3D Printed Metals



Undertake materials characterisation activities on 3D printed metals. The project will require the

student to design and familiarise themselves with the manufacture of test specimens, and

additionally design and conduct mechanical testing on the specimens. Specific unique designs will

also be nominated to the student for investigation. The student will be required to have a solid

understanding of materials and finite element software, and compare the analytical and test results.

The testing will need to consider various factors controllable in the additive manufacturing process

such as build speed, laser power, powder size, part orientation, support type and part design.

Project Objectives:

1. Document the mechanical properties of 3D printed metals taking into account factors

controllable in the additive manufacturing process

2. Investigate the mechanical strength of various unique designs and compare the analytical and

test results

Project Activities:

1. Develop a test plan for mechanical characterisation of 3D printed metals taking into account

factors controllable in the additive manufacturing process

2. Undertake mechanical testing to determine mechanical characteristics of 3D printed metals.

3. Undertake structural analysis and mechanical testing of various unique designs, and compare

the results.

4. Document all activities conducted in a project report

5. Present a 6 minute ‘pitch’ presentation at the Defence Science Student Conference 2017 and to

relevant engineers or researchers within DST Group.

WCSD SVP 01: Cooperative and Coordinated Strike with Multiple

Networked Weapons



Modern strike weapons are becoming increasingly less effective against complex defensive systems.

Missions are primarily planned in advance offline without much ability to respond intelligently to a

complex and dynamically changing battlespace. However, next generation weapons will be highly

networked, with access to far more information from internal and external sensors than ever before.

They will have access to far more processing power and a swathe of machine learning and decision

making algorithms.

Coordinated weapons have the potential to improve the cost benefit ratio of a given system of

weapons systems by employing techniques such as simultaneous or staggered time-on-target, multi-

directional attack, online target allocation and reallocation and deceptive manoeuvres, all of which

could be configured on the fly in complex battlespace.

This project will involve development of concepts, algorithms and models in the context of game

between a land or sea based air defence system and a coordinated aerial assault.

Project Objectives:

1. Modelling of decentralised online task allocation functions in complex many on many combat

scenarios;

2. Modelling of consensus based multi-weapon control algorithms to enable cooperative

engagement using a mix of soft-kill and hard-kill weapons; and

3. Intelligent planning and control of multi weapon systems using machine learning approaches.

Project Activities:

Students working on this project will be involved in the development of concepts and algorithms for

inter-weapon cooperation, and the construction of software models to implement these algorithms.

Students will need to be able to contribute effectively to a team which collectively should have

strong MatLab and Simulink skills, experience in the modelling of aerospace systems (particularly in

the areas of dynamics and control) and experience in relevant mathematical or computer science

areas such as Game Theory, Data Fusion or Machine Learning.

The breakdowns of activities are:

1. Development of decentralised task allocation algorithms;

2. Generation of Electronic Attack (EA) models for the many on many simulation framework (MSF) in

DST Group;

3. Development of machine learning based tactics and guidance algorithms;

4. Multi Agent System framework upgrade; and


WCSD SVP 02: Upgrade of Heat Treatment Furnace: PC Control



The project is focused on upgrading a heat treatment furnace to PC Control for programming and

data logging purposes. The project will include research and implementation of LabVIEW to create a

User Interface for programming and logging the furnace operation. Demonstration of oven

functionality will be performed using simple tests pieces with pre and post-hardness testing.

Project Objectives:

1. Develop and demonstrate research skills;

2. Design and implement PC Control of scientific instrument; and

3. Document results and present findings.

Project Activities:

1. Conduct research into software and furnace controller;

2. Develop User Interface to allow programming and data logging;

3. Demonstrate operation of oven using sample heat treatment process and conduct hardness

testing;

4. Documentation e.g. User Manual;

5. Suit Engineering or Materials Science Student or similar. Simple programming knowledge is

necessary; experience with LabVIEW is desirable but not a pre-requisite; and

6. Present a six minute ‘pitch’ presentation to the Defence Science Student Conference 2017.

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