Recently, researchers have considered the application of multiple-input multiple-output (MIMO) techniques developed for wireless communication systems to the radar scenario. In MIMO systems, multiple antennas are employed at both transmitter and receiver to increase the data rate and reduce the effect of rapid changes in the radio channel with time. In the context of radar systems, mono-static or bi-static MIMO radars could be used to reduce the impact of scintillation effects, by illuminating the target from multiple transmit antennas but with the same total transmitter power budget. MIMO radars could also reduce the search time to find targets by transmitting multiple waveforms simultaneously, which allows more efficient searching of transmit angle. Further, MIMO processing increases the effective degrees of freedom in the radar system and may thus increase tolerance to echoes from the ground in radar systems and from the sea floor in sonar systems as well as deliberate man/made sources of interference. Since the emergence of MIMO radar concept international activity has focused both on the underlying theory, confirming the significant potential gains in detection and resolution performance that might be achieved, and on developing signal processing algorithms to facilitate these gains. What we propose here is to exploit the work we have already done in (i) methodologies for calculating detection performance in realistic MIMO radar or sonar scenarios; (ii) adaptive detection techniques for radar array-based signal processing that do not require secondary training data. We address the open research questions whose solution will facilitate industrial exploitation of the MIMO radar concept. In particular these are: (i) the design of correlation controlled constant amplitude MIMO waveforms; (ii) the development of adaptive receiver algorithms capable of working in environments of unknown clutter statistics and within the constraints of limited bandwidth communication channels between individual TR/RX pairs. A further novel aspect of the work will be the application of and assessment of MIMO concepts in sonar environments. What we propose is a rigorous generic approach to the understanding and application of MIMO detection. The results will be tested and validated in radar and sonar applications using detailed computer modelling techniques for both target and the medium. In the sonar case they will also be tested with measured data.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

The increasing use of unmanned aerial vehicles (UAVs) has spanned from the military domain to a wide range of civilian applications in recent years. Among many different types of UAVs, helicopters (or rotorcraft in general) have dominated in many applications because of their unique capabilities of hovering, low speed cruise and vertical take-off and landing (VTOL). Example applications can be easily found in aerial photography, film making and infrastructure inspection. However, unlike their full size counterparts, only few examples of using unmanned helicopters in maritime environments can be found, although the potential benefits of the rapid deployment, cost reduction and mission flexibility are great. The main challenge here is to land an unmanned helicopter accurately and safely on the deck of a ship, which needs to be conducted in an adverse maritime environment, such as external disturbances, ship movement and confined operational space. This project aims to tackle this challenge by developing an integrated control framework for systems operated in adverse environments. It not only relies on traditional feedback mechanisms based on control errors, but is also able to anticipate environmental influences on the system dynamics and rectify them proactively. Specifically, by consolidating two powerful control concepts (i.e. disturbance observer based control and model predictive control) and further expanding their capabilities, the developed control framework will be able to deal with the complicated helicopter dynamics and to take into account the external disturbances from different sources, so as to improve the control accuracy and robustness. The development of this integrated control framework will be complemented by rigorous theoretical analysis and validated by realistic flight tests under adverse conditions. In the light of the recent government promotion of maritime autonomous systems, the proposed research to enable autonomous landing of a helicopter on the deck of a ship would bring the advantages of unmanned helicopters into a vast range of applications in the maritime environment. This will complement surface and undersea maritime vehicles to form a truly 3-D autonomous capability at sea. Tasks such as environment monitoring, surveillance of vessel traffic and migrant flows, and cargo supply can be more efficiently performed by unmanned helicopters with modest cost. Allowing them to operate in adverse weather conditions will significantly improve their reliability and reduce the risks in the maritime environment. The proposed control framework will also play a critical role in fully exploring helicopters' VTOL capability in those tasks, for example to deliver humanitarian aid to boats with refugees and acquire samples from chemical or oil spills at sea, where precise manoeuvres are required. Moreover, it is envisaged that the proposed control strategy can be used as a control synthesis tool not only for other types of small/micro UAVs in adverse conditions, but also in other application domains like autonomous surface vehicles, where disturbance impacts on system dynamics are also significant.

Commercial and government decisions are driven by data. Provenance is the record of how data and processes were created, modified and used. It is used to support quality assessments for data, provide traceability, identify possible system intrusions, etc. Unfortunately, all of the uses of provenance require that provenance information be captured by each system within a system of systems. This "capture problem" is costly and does not scale. To date, only applications that have a high value to scientists have been provenance capture-enabled [9, 17]. Instead, we seek to build observation points external to any pre-built system that will create partial, or inferred, provenance that can be reused across any system that uses the same architectural components. In order to facilitate the adoption of provenance within enterprise systems built from a heterogeneous software stack that is unique to each organization, the Infer-Proven-ence project is researching the underlying feasibility and creating a toolbox of techniques that will reduce the number of applications that must be provenance-enabled. Unlike a provenance-enabled application that can report observed provenance, inferred provenance has a probability of being what actually happened. Depending on the overall architecture, different provenance inference techniques need to be available. An inference technique that works within a database and its limited set of transformations will not work over streaming data. This work is establishing the theoretical underpinnings for two different provenance-capture inference mechanisms that work within common architectures. It will create implementations of each technique that can be evaluated within real-world scenarios. The Infer-Proven-ence approach shall be evaluated across two distinct architectures: one for stream processing, and one for data analytics. While architectures exist that combine all of these components, we intentionally split them into the smallest representative unit with respect to data flow and application-type. With this in mind, Infer-Proven-ence will be evaluated across two distinct architectures: a stream processing of sensor data architecture; and a data analytic architecture. Evaluation will consider: ability to correctly infer provenance; accuracy of inferred provenance; cost of implementation within the given architecture, scalability of approach and the utility of the inferred provenance for a use case specific to each problem domain. For the first technique, we will work with partners at Roke Manor Research and their autonomous vehicle program in which data from disparate sensors is streamed through a set of micro-processors and driving decsions are made. Provenance within this use case will be used to highlight anomalies and likely sources of decision errors. For the second technique, we will work within a data analytic architecture in which source data is transformed and manipulated during the process of analysis. Provenance within this use case will be used to reproduce the analytic results In addition to the real-world evaluation, we shall work closely with UK's Software Sustainability Institute, which promotes sustainable software technologies in order to build software that can be transitioned and reused by others. SSI shall assist in ensuring that Infer-Proven-ence is generalizable and relevant to any discipline based only on the architecture required by that discipline. Finally, Infer-Proven-ence will produce a roadmap for further research, taking stock of the work done and identifying future opportunities. Infer-Proven-ence also builds partnerships across several institutions including Southampton's Cyber Security Research Centre, the University of Massachusetts Amherst, the Software Sustainability Institute and Roke Manor Research in order to investigate provenance inference in real-world situations.

Wireless access is an essential to the networks that underpin modern life, providing communications for people, vehicles, machines, infrastructure, and the wide variety of devices that will make up the Internet of Things (IoT). They will become increasingly important to support safe transportation and future healthcare. Society is increasingly vulnerable to network cyber attack, for motivations ranging from financial extortion through terrorist disruption to subversion. Cyber attacks can be mounted remotely through networks, making them attractive to malefactors who can operate safely and anonymously from anywhere in the world. Cyber defence and associated research has become critical, mainly directed at developing and rolling out technical encryption and authentication measures in the network protocols and embedding the essential processes in organisations. Nevertheless exploits continue as attackers discover new vulnerabilities that were not considered in the system design or arise through imperfect implementations. Fixing these requires updating both functionality and credentials of the network elements as threats emerge. By contrast cyber-attack via the wireless interface, exploiting vulnerabilities in the physical layer and lower layers of the protocol stack, has received much less attention. As network originated exploits become more difficult it can be expected that more attacks will be mounted through the "air interface". The means to develop and mount such attacks are increasingly available with the proliferation of low cost software-defined radio (SDR) platforms and open-source software, and the ubiquity of potentially hackable wireless terminals. More research on this problem is needed to find solutions to be retrospectively applied to existing systems, influence the next generation of wireless standards, raise awareness of the potential problems, and train engineers to develop and embed defensive capability in radio standards and products. Crucial will be the ability to change the physical layer functionality, right to the antenna, by changing system software. This is not possible with current equipment or indeed envisaged in the 5G. Apart from countering the security threat, such technology will be needed to enable the future adoption of Dynamic Spectrum Access (DSA), in which, rather than frequency bands being administratively licensed to specific users, spectrum will be allocated dynamically according to evolving demand in space and time. The project partners, Toshiba Research, Roke, University of Bristol, and GCHQ, share a vision of Secure Wireless Agile Networks (SWAN) to be developed in this research partnership. The project scope will include technical deliverables; the shaping of policy and standards; and the training and career development of the SWAN teams. The co-created 5-year programme will integrate academic and industrial teams in activities that address the following Research Challenges (RCs). 1. Threat Synthesis & Assessment: how can RF interfaces be attacked, beyond the threats envisaged in their design? 2. RF Cyber Detection & Defence: techniques to detect RF cyber attack and mitigate their effects. 3. Cyber Secure Radio Design: designing radios whose RF characteristics can be updated in the field to deal with new threats, which also enable DSA. 4. Secure Dynamic Spectrum Access: enabling technology for securely sharing spectrum for most efficient usage. The consequences of not addressing the above will potentially make the wireless channel an Open Attack Surface for cyber attack. SWAN's technological solutions will place the UK at the forefront of enabling the fundamental parameters and architectures of wireless systems to be adaptable to new spectrum and interface specifications; resilient to accidental or induced failures (such as jamming); and resistant to cyber-attack.