ABOUT THE DIN

Predictive Target Tracking and Sensor Fusion Model 

RedTail Technology 

About the Company

RedTail Technology (RTT) is a small Australian defence startup specialising in the integration of AI/ML with lasers and optics to build autonomous electro-optic systems. RTT has a proven record of delivering operationally relevant solutions to Defence’s most challenging problems. Its current focus is the Katoomba counter-uncrewed aerial system (C-UAS) — an AI-infused, lightweight directed-energy protection system for critical infrastructure and Defence applications against hostile or unauthorised UAS platforms.

Project Objective

The Katoomba Counter-small UAS (C-sUAS) aim-assist system requires highly precise target tracking to maximise laser time-on-target and improve operational efficiency. As a hand-held device operated under high cognitive load, both target and platform motion must be modelled using high-frequency optical, inertial, ranging and behavioural sensor data. This project will research and develop a real-time micro-predictive framework to outpace system software and mechanical latencies — improving the system’s ability to track tiny, rapidly manoeuvring drones and directly enhancing warfighter survivability. 

Project Tasks

• Sprint 1: Analyse IMU data for predictive analysis and stabilisation techniques; develop models and scripts for 100s-microsecond prediction of unintentional system movements. 

• Sprint 2: Analyse optical and other sensor data to model and predict target future position; develop models and scripts for 100s-microsecond target position prediction. 

• Sprint 3: Develop extended joint models for dual system stabilisation and target position tracking; integrate models into a program to run on the RTT Katoomba platform. 

• Sprint 4: Further subsystem integration and optimisation for high-speed execution on a GPU-enhanced edge device; deliver a final research report detailing approaches attempted, outcomes, challenges and ideas for future improvement. 

Intern Skills

• Advanced AI/ML skills and experience with custom neural network design. 

• Sensor fusion techniques such as Kalman filters. 

• Experience processing data on low-power or edge computing systems (desirable). 

• Python programming; Git. 

• Creative, out-of-the-box thinker with interdisciplinary problem-solving ability. 

• Interest in national defence and autonomous systems. 

• Must be an Australian citizen; a National Police Background Check, Non-Disclosure Agreement and IP assignment agreement are required. 

How to apply

Eligible students (Australian citizens) apply via the online application form and submit a CV and motivation letter by 6 September 2026.