Sensor Data Fusion and Image Processing to Enhance Panoramic Infrared Search and Track (IRST) System

Location: Sydney, NSW

Duration: 5 months

Proposed start date: ASAP

Please note: Due to the sensitivity and security of this project, students must have Australian Citizenship to apply. Any applicants not meeting this requirement will automatically be deemed ineligible for this project.

Project Background

Safran Electronics and Defense Australasia is undertaking a project to explore concepts to improve the capability of IRST technology.

Safran Defense are seeking a PhD student with expertise and practical skills in state of the art image processing and data fusion. Specifically they will be looking at how to make use of geographic/positional data, and / or other sensor inputs to inform selective filtering / image segmentation of land/coastal backgrounds in panoramic infrared images.

Further the intern will be asked to develop prototype tracking algorithms optimised for application on challenging land backgrounds. An interesting aspect of this part of the project will be discrimination of low contrast targets against high noise, ‘cluttered’ backgrounds.

The research undertaken will be a desk based study using best available tools. In developing the algorithms no consideration needs be given to system performance limits or integration of the developed code onto actual hardware.

Research to be Conducted

  • Prototype, evaluate and report on the feasibility a number of data fusion (i.e. non image processing based) approaches to coastal area land detection in IRST images
  • Develop, refine and validate the efficacy of various algorithms to track moving targets on coastal/land backgrounds in IRST images, propose the most effective approaches given system limitations

Skills Required

We are looking for a PhD student with the following:

ESSENTIAL

  • In Computer Science, Software Engineering or related field
  • High level knowledge and expertise in image processing using Matlab

DESIRABLE

  • OpenCV (C++ or Python) is also beneficial

Expected Outcomes

A report detailing current state of the art, the areas investigated and any prototyping done including recommendations on the feasibility and next steps required for further investigation.Theoretical models of how to identify land/coastal areas in infrared images using data fusion approach and ideally some simple prototype models of the most promising option(s)

Prototype tracking algorithms and a report outlining the efficacy vs false detection rate and recommendations for improvement and optimisation.

If the project objectives are met Safran Electronics and Defence Australasia will use the new knowledge to better understand the development pathway toward the future of IRSTequipment. This new knowledge will contribute to the roadmap for new software & electronics development.

Additional Details

The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.

It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 80% of their time on-site with the industry partner.  The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.

The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.

Applications Close

26 June 2019

Reference

APR – 0812