The Microwave Integrated Systems Laboratory at the University of Birmingham is offering a PhD studentship with Thales UK as part of their recently awarded Industrial Cooperative Award in Science & Technology (iCASE). Funded by the Engineering and Physical Sciences Research Council, the Industrial CASE award aims to provide PhD students with a first-rate, challenging research training experience, within the context of a mutually beneficial research collaboration. Manned and unmanned airspace is undergoing a revolution. By 2030, air traffic is estimated to quadruple with a doubling of the total number of manned aircraft and unmanned air vehicles (UAVs). This growth will greatly change already heavily used airspace.
At the same time, there is likely to be an increasing dependency on renewable sources of energy. Windfarms will play a major role in future energy provision and themselves occupy low-level airspace both on and off-shore. Detection of air targets over windfarms at assurance levels compliant with airspace regulations is challenging for current radars with the type of clutter encountered. In addition, UAVs occupy airspace in a similar way to birds with both flying at overlapping altitudes and velocities. As evidenced by recent drone incursions at Gatwick airport, there is a pressing need to be able differentiate UAVs from natural organisms (e.g. birds) that use the same airspace.
Traditionally, the vast majority of radar sensors have been monostatic, transmitting and receiving through a single aperture. Limits of achievable performance are being reached. Networked radar sensing offers a way to improve overall system sensitivity, enhancing detection range, tracking and classification performance. To maximise these improvements new methods of network-specific, “cognitive” signal processing need to be developed. Such systems and algorithms will have to be able to adapt radar parameters and signal processing algorithms ‘on-the-fly’ as well as being able to generate and exploit ‘memories’ (from predecessor pulse echoes) in order to tailor the system response to provide best performance at any given time and in any given location within the field of regard.
The aim of the PhD is thus to research novel but potentially applicable system, waveform and signal processing techniques to mitigate high complexity clutter environments for airborne target detection, tracking and characterisation using networked radar systems. The research will be experimentally supported by an advanced form of a radar network using two, coherent Thales-Aveillant Gamekeeper systems, implemented at the University of Birmingham under the Quantum Technology Hub programme. This research facility will comprise two all-digital receive arrays, high capacity processing and large data memory (for retrospective and ‘memory’ processing). This unique facility will provide an experimental environment to explore advanced signal processing algorithms developed as part of this PhD.
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