Signal Processing Solutions for the Networked Battlespace

The nature of the modern battlefield is changing dramatically. Electronic communication is allowing unprecedented interchange of data and information between platforms. Advances in electronics are allowing the possibility of low cost networked unattended sensors. Intelligent and robust processing of the very large amount of multi-sensor data acquired from various networked communications and weapons platforms is, therefore, crucial to retain military advantage and mitigate smart adversaries who present multiple threats within an anarchic and extended operating area (battlespace). Hence we have composed a unique consortium of academic experts from Loughborough, Surrey, Strathclyde and Cardiff universities together with six industrial project partners QinetiQ, Selex-Galileo, Thales, Texas Instruments, PrismTech & Steepest Ascent, to develop transformational new signal processing solutions to the benefit of Dstl, the MoD, and the UK in general.

To achieve this goal we are proposing a five-year integrated programme of work composed of the following five interlinked work packages: (1) Automated statistical anomaly detection and classification in high dimensions for the networked battlespace, in which we aim not only to detect anomaly, but also to identify its nature and nuance, when acquired in a high dimensional complex network environment. Data quality and ambiguity measures will be used to ensure the models of normality are not corrupted by unreliable and ambiguous data; (2) Handling uncertainty and incorporating domain knowledge, within which we aim to exploit the world model of the networked battlespace to improve performance and confidence, and to reduce uncertainty to an unprecedented level. Examples for such information are digital maps about terrain and layout of the field, geometric relations between platforms and operational conditions such as weather; (3) Signal separation and broadband distributed beamforming, in which we target at designing low-complexity robust algorithms for underdetermined and convolutive source separation, and broadband distributed beamforming, facilitated by low-rank and sparse representations, and their fast implementations; (4) Multi-input and multi-output (MIMO) and distributed sensing, within which we intend to create novel paradigms for distributed MIMO radar systems operating in the cluttered networked battlespace; and (5) Low complexity algorithms and efficient implementation, in which with Texas Instruments, PrismTech & Steepest Ascent we aim to formulate and realize novel implementation strategies for a range of complex signal processing algorithms in a networked environment. These interlinked workpackages have been very carefully designed to marry up with the research themes and challenges identified by Dstl & the EPSRC and we have clear strategies for attaining datasets, performing evaluation, and communicating findings.

We have designed a carefully structured consortium management team including an overarching steering group with renowned external independent experts with expertise covering the scope of the work programme. The operation of the consortium will be the responsibility of the Consortium Director and the Consortium Management Team. A key component of our consortium management is to encourage research staff and students employed to be periodically seconded to the labs of other collaborators within the consortium to benefit from complementary knowledge and skills at partner universities and industry; gain access to privileged datasets and/or equipment; or share resources & provide critical mass when addressing a particular Dstl challenge.

The management structure and coordination measures have been designed for the consortium to have the capacity to assume the role of lead consortium, if required, working with Dstl & EPSRC to establish a community of practice in signal and data processing, and to ensure the UK has world leading capability in the area.

The proposed research will likely generate wide impact on knowledge, people, economy and society:-

Knowledge.
Advances in anomaly detection, handling uncertainty, enhancement of broadband signal processing through polynomial matrix linear algebra, and novel distributed cognitive radar will lead to new methods and underline what is scientifically possible. The delivery of efficient implementations will advance the current state-of-the-art of military equipment and demonstrate what can be technically feasible given state-of-the-art computational resources. We aim to make this knowledge gain accessible through our Resource Centre and dissemination activities ranging from publications in internationally leading journals to seminars, summer schools, and similar events.

Training and Education.
We aim to educate internally, and contribute to education and staff development externally, to create a cohesive and innovative research community spanning from the consortium to Dstl, the industrial project partners, and the wider research and engineering community, particularly if selected as the lead consortium. The collaborative nature of this project will see PDRAs involved across various work packages and partner universities. Through secondments and internships at industrial partners, a wider skill set will be encouraged in PDRAs and PhD students. Dstl staff and industrial partners will benefit from close involvement with various parts of the project, and interaction with researchers during seminars, internships and secondments, which is expected to lead to a transfer of knowledge and capabilities.

Economy.
The implementation component of the proposed research and applicability based on relevant data sets is expected to lead to benefits for Dstl, the MoD, military sector stakeholders and for the UK economy. Particularly through working with key industrial partners including QinetiQ, Selex-Galileo, Texas Instrument, Thales, PrismTech and Steepest Ascent, we will ensure that there are conduits for further exploitation. Impact will be generated through grounding of our research in real and relevant defence problems and its application to relevant data sets, through close linkage with Dstl and our industrial partners. Escalation of our research effort to knowledge exchange activities will be guided by a technology push from the consortium partners and a technology pull by Dstl and our industrial partners.

Society.
The proposed research will provide an advantage in strategic and tactical military operations involving different military units composed, for example, of the UK MoD and military forces of other nations when they are engaged in a coalition for international peace-keeping missions. With the UK MoD being one of the major beneficiaries of the proposed project, our work will have impact on the UK's security. The consortium will maintain an easily accessible online resource or utilise social media, where the results of our research are explained for the policy stakeholders and the wider public.

Overall, the impacts of our proposed research will offer new business opportunities for wealth creation and maintain the UK's scientific and technological competitiveness in defence signal processing, thereby ensuring that the EPSRC's targets to grow the UK's capability in digital signal processing and to attain an intelligent information infrastructure are met. This will also help to ensure the Defence Technology Strategy for the 21st Century is implemented.