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A fully funded PhD studentship (and funding for 4 years and funded by DSTL, UK) is currently available in Cognitive Radar within Autonomous systems. The funding arrangements are such that it is only available to UK/ EU Nationals and at Queen’s University of Belfast, UK.

Starting date: January 2012

Description of the problem: Autonomous systems are required to gain knowledge about their environment through data collection and processing so they can make decisions about future actions in order to achieve their goals. The robustness of the decisions made is primarily dependent on the measurements of the environment and the quality of the exploitation of this data, and therefore this situational analysis is critical to the success of the autonomous system as a whole. Radar is one such sensor platform which is often vital for this purpose, and allows robotic and automated systems to work with beyond-human capabilities, due to the radar’s capacity to operate in low visibility environments and provide imaging of sub-surface features such as ground penetrating radars (GPR) which has a wide variety of applications, some examples include geological investigations of terrain for mineral ores and planetary exploration, condition of engineered structures, such as bridges, railway tracks and beds and landmine detection, and therefore improvements in the field have high impact on a large number of activities. Further, the radar actively probes its environment and therefore can extract information that is required if used appropriately, but to make this ground-breaking step to be able to autonomously generate awareness, predict actions, schedule sensing, and aggregate sensor data intelligently, the radar system itself has to be cognitive or intelligent in its nature.
High impact applications include autonomous GPR, robotics and real-time sensor networks which can be used for autonomous environmental monitoring of physical and biological indicators, tactical surveillance, disaster prevention, undersea exploration, unmanned navigation, etc. Compared to the significant progress in the application of computer vision based intelligent system design, there is less progress reported to date on studying cognitive radar and related fields such as cognitive sonar. Therefore, this proposal will enhance the effectiveness of field capabilities of radar technology as well as will produce potential for disruptive technologies.

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