- Dr Jason Ford
- Senior Lecturer in Electrical Engineering
Science and Engineering Faculty,
Electrical Engineering, Computer Science,
Robotics and Autonomous Systems
- Discipline *
- Electrical and Electronic Engineering, Aerospace Engineering
- +61 7 3138 2207
- View location details (QUT staff and student access only)
- Social Media
Doctor of Philosophy (Australian National University), Bachelor of Engineering (Australian National University), Bachelor of Science (Australian National University)
- Professional memberships
signal processing, control
Jason J. Ford is a senior lecturer in electrical engineering at Queensland University of Technology.
Biography: Jason received the B.Sc., B.E., and Ph.D. degrees from the Australian National University, in 1995 and 1998. In 2005 he joined the Queensland University of Technology.
Recent research highlights include:
- Development of automation systems for infrastructure inspection aircraft within the ROAMES asset management system. ROAMES aircraft are currently operational and inspecting infrastructure on three continents, and has created value benefits estimated to exceed $221M (out to 2024).
- Several world firsts in vision based sense and avoid systems for UAS technology.
Jason’s current research interests include robust and non-fragile signal processing and control for autonomous systems.
- Molloy TL, Ford JJ, (2015) Towards strongly consistent online HMM parameter estimation using one-step Kerridge inaccuracy, Signal Processing p79-93
- Lai JS, Ford JJ, Mejias Alvarez LO, O'Shea PJ, (2013) Characterization of sky-region morphological-temporal airborne collision detection, Journal of Field Robotics p171-193
- Techakesari O, Ford J, (2013) Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems, Signal Processing p12-22
- Lai JS, Ford JJ, O'Shea PJ, Mejias Alvarez LO, (2013) Vision-based estimation of airborne target pseudobearing rate using hidden Markov model filters, IEEE Transactions on Aerospace and Electronic Systems p2129-2145
- Mejias Alvarez L, Lai J, Ford J, O'Shea PJ, (2012) Demonstration of closed-loop airborne sense-and-avoid using machine vision, IEEE Aerospace and Electronic Systems Magazine p4-7
- Techakesari O, Ford J, Nesic D, (2012) Practical stability of approximating discrete-time filters with respect to model mismatch, Automatica p2965-2970
- Lai J, Mejias Alvarez LO, Ford JJ, (2011) Airborne vision-based collision-detection system, Journal of Field Robotics p137-157
- Bruggemann TS, Ford JJ, Walker RA, (2011) Control of aircraft for inspection of linear infrastructure, IEEE Transactions on Control Systems Technology p1397-1409
- Lai J, Ford JJ, (2010) Relative entropy rate based on multiple hidden Markov model approximation, IEEE Transactions on Signal Processing p165-174
- Ford JJ, Ugrinovskii VA, (2008) Robust Control of Nonlinear Jump Parameter Systems Governed by Uncertain Chains, IEEE Transactions on Automatic Control p1520-1526
For more publications by this staff member, visit QUT ePrints, the University's research repository.
Grants and projects (Category 1: Australian Competitive Grants only)
- Automated vision-based aircraft collision warning technologies
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- Start year
- Collision Warning, Aerial robotics, National Airspace
Completed supervisions (Doctorate)
- Online Hidden Markov Model Parameter Estimation and Minimax Robust Quickest Change Detection in Uncertain Stochastic Processes (2015)
- Filter and control Performance Bounds in the Presence of Model Uncertainties with Aerospace Applications (2013)
- Visual guidance for fixed-wing unmanned aerial vehicles using feature tracking : application to power line inspection (2013)
- A Hidden Markov Model and Relative Entropy Rate approach to Vision-based Dim Target Detection for UAV Sense-and-Avoid (2010)
- Robust Adaptive Control of Rigid Spacecraft Attitude Manoeuvres (2008)