Sensors have for a long time played a vital role in battle awareness for all our armed forces, ranging from advanced imaging technologies, such as radar and sonar to acoustic and the electronic surveillance. Sensors are the "eyes and ears" of the military providing tactical information and assisting in the identification and assessment of threats. Integral in achieving these goals is signal processing. Indeed, through modern signal processing we have seen the basic radar transformed into a highly sophisticated sensing system with waveform agility and adaptive beam patterns, capable of high resolution imaging, and the detection and discrimination of multiple moving targets. Today, the modern defence world aspires to a network of interconnected sensors providing persistent and wide area surveillance of scenes of interest. This requires the collection, dissemination and fusion of data from a range of sensors of widely varying complexity and scale - from satellite imaging to mobile phones. In order to achieve such interconnected sensing, and to avoid the dangers of data overload, it is necessary to re-examine the full signal processing chain from sensor to final decision. The need to reconcile the use of more computationally demanding algorithms and the potential massive increase in data with fundamental resource limitations, both in terms of computation and bandwidth, provides new mathematical and computational challenges. This has led in recent years to the exploration of a number of new techniques, such as, compressed sensing, adaptive sensor management and distributed processing techniques to minimize the amount of data that is acquired or transmitted through the sensor network while maximizing its relevance. While there have been a number of targeted research programs to explore these new ideas, such as the USs "Integrated Sensing and Processing" program and their "Analog to Information" program, this field is still generally in its infancy. This project will study the processing of multi-sensor systems in a coherent programme of work, from efficient sampling, through distributed data processing and fusion, to efficient implementations. Underpinning all this work, we will investigate the significant issues with implementing complex algorithms on small, lighter and lower power computing platforms. Exemplar challenges will be used throughout the project covering all major sensing domains - Radar/radio frequency, Sonar/acoustics, and electro-optics/infrared - to demonstrate the performance of the innovations we develop.

Our vision is to rejuvenate modern electronics by developing and enabling a new approach to electronic systems where reconfigurability, scalability, operational flexibility/resilience, power efficiency and cost-effectiveness are combined. This vision will be delivered by breaking out of the large, but comprehensively explored realm of CMOS technology upon which virtually all modern electronics are based; consumer and non-consumer alike. Introducing novel nanoelectronic components never before used in the technology we all carry around in our phones will introduce new capabilities that have thus far been unattainable due to the limitations of current hardware technology. The resulting improved capability of engineers to squeeze more computational power in ever smaller areas at ever lower power costs will unlock possibilities such as: a) truly pervasive Internet-of-Things computing where minute sensors consuming nearly zero power monitor the world around us and inform our choices, b) truly smart implants that within extremely limited power and size budgets can not only interface with the brain, but also process that data in a meaningful way and send the results either onwards to e.g. a doctor, or even feed it back into the brain for further processing, c) radiation-resistant electronics to be deployed in satellites and aeroplanes, civilian and military and improve communication reliability while driving down maintenance costs. In building this vision, our project will deliver a series of scientific and commercial objectives: i) Developing the foundations of nanoelectronic component (memristive) technologies to the point where it becomes a commercially available option for the general industrial designer. ii) Setting up a fully supported (models, tools, design rules etc.), end-to-end design infrastructure so that anyone with access to industry standard software used for electronics design today may utilise memristive technology in their design. iii) Introduce a new design paradigm where memristive technologies are intimately integrated with traditional analogue and digital circuitry in order to deliver performance unattainable by any in isolation. This includes designing primitive hardware modules that can act as building-blocks for higher level designs, allowing engineers to construct large-scale systems without worrying about the intricate details of memristor operation. iv) Actively foster a community of users, encouraged to explore potential commercial impact and further scientific development stemming from our work whilst feeding back into the project through e.g. collaborations. v) Start early by beginning to commercialise the most mature aspects of the proposed research as soon as possible in order to create jobs in the UK. Vast translational opportunities exist via: a) The direct commercialisation of project outcomes, specifically developed applications (prove in lab, then obtain venture capital funding and commercialise), b) The generation of novel electronic designs (IP / design bureau model; making the UK a global design centre for memristive technology-based electronics) and c) Selling tools developed to help accelerate the project (instrumentation, CAD and supporting software). Our team (academic and industry) is ideally placed for delivering this disruptive vision that will allow our society to efficiently expand the operational envelope of electronics, enabling its use in formidable environments as well as reuse or re-purpose electronics affordably.

Our vision is to rejuvenate modern electronics by developing and enabling a new approach to electronic systems where reconfigurability, scalability, operational flexibility/resilience, power efficiency and cost-effectiveness are combined. This vision will be delivered by breaking out of the large, but comprehensively explored realm of CMOS technology upon which virtually all modern electronics are based; consumer and non-consumer alike. Introducing novel nanoelectronic components never before used in the technology we all carry around in our phones will introduce new capabilities that have thus far been unattainable due to the limitations of current hardware technology. The resulting improved capability of engineers to squeeze more computational power in ever smaller areas at ever lower power costs will unlock possibilities such as: a) truly pervasive Internet-of-Things computing where minute sensors consuming nearly zero power monitor the world around us and inform our choices, b) truly smart implants that within extremely limited power and size budgets can not only interface with the brain, but also process that data in a meaningful way and send the results either onwards to e.g. a doctor, or even feed it back into the brain for further processing, c) radiation-resistant electronics to be deployed in satellites and aeroplanes, civilian and military and improve communication reliability while driving down maintenance costs. In building this vision, our project will deliver a series of scientific and commercial objectives: i) Developing the foundations of nanoelectronic component (memristive) technologies to the point where it becomes a commercially available option for the general industrial designer. ii) Setting up a fully supported (models, tools, design rules etc.), end-to-end design infrastructure so that anyone with access to industry standard software used for electronics design today may utilise memristive technology in their design. iii) Introduce a new design paradigm where memristive technologies are intimately integrated with traditional analogue and digital circuitry in order to deliver performance unattainable by any in isolation. This includes designing primitive hardware modules that can act as building-blocks for higher level designs, allowing engineers to construct large-scale systems without worrying about the intricate details of memristor operation. iv) Actively foster a community of users, encouraged to explore potential commercial impact and further scientific development stemming from our work whilst feeding back into the project through e.g. collaborations. v) Start early by beginning to commercialise the most mature aspects of the proposed research as soon as possible in order to create jobs in the UK. Vast translational opportunities exist via: a) The direct commercialisation of project outcomes, specifically developed applications (prove in lab, then obtain venture capital funding and commercialise), b) The generation of novel electronic designs (IP / design bureau model; making the UK a global design centre for memristive technology-based electronics) and c) Selling tools developed to help accelerate the project (instrumentation, CAD and supporting software). Our team (academic and industry) is ideally placed for delivering this disruptive vision that will allow our society to efficiently expand the operational envelope of electronics, enabling its use in formidable environments as well as reuse or re-purpose electronics affordably.

Digital signal processing is a powerful technique for storing, analysing and manipulating digital signals. Ultimately, the quality of the signal to be processed is determined by the performance of the analogue-to-digital converter (ADC) which is used to sample the original analogue signal in the first place and produce a digital representation of it. Electronic ADCs are embedded ubiquitously in numerous everyday items, such as mobile phones, digital thermometers and computer mice to name a few. As the speed of electronic ADCs continues to increase, more and more sophisticated applications including medical imaging and cognitive radar can benefit from the use of ADCs and digital signal processing. Photonics has been used to increase the performance of electronic ADCs since the 1970s, forming what is now generally termed the photonic ADC. Most photonic ADCs with sampling rates as high as 1 THz (1,000,000,000,000 Hz) have invariably employed mode-locked lasers as they can produce very high power optical pulses with very short pulse widths and low jitters, both in the femto second region. Such ultra-short and stable optical pulses are ideal for sampling microwave and millimetre-wave signals at a sampling rate which is beyond what is achievable using conventional electronic ADCs. However, most mode-locked laser sources are bulky, expensive and require constant stability adjustments. Therefore they have not found widespread commercial application to date. Furthermore, the repetition rates of most mode-locked laser pulse sources cannot be readily adjusted and as a result, the sampling rates of photonic ADCs using such sources are fixed and cannot be varied to suit the input signal frequency and bandwidth. In this application, we seek support to investigate a new, high-performance photonic sampling technique based on an optical comb generator instead of the traditional mode-locked lasers. In this novel approach, continuous sampling at flexible sampling frequencies are possible, unlike the mode-locked laser approach. We have also calculated that the combined jitter level due to the linewidth of a typical DFB laser and the phase noise of a mm-wave generator to be used in this technique is less than 5 fs (RMS) and the corresponding effective number of bits (ENOB) of resolution is 10 which is superior to the state-of-the-art CMOS electronic ADC and the all-optical ADC at the same 40 GHz sampling frequency. Such high-performance photonic sampling technique is expected to attract wide attention from both the research community and the industry.

Protection of homeland territory, offshore and overseas assets and related national economic and political interests are strategically important priorities for the UK and the world community. Worldwide economical and political crisis over the last few years has deepened this challenge and the UK witnesses the consequences of it, resulting in increased illegal immigration entries, piracy, and threats to commercial and national assets. Technological advances become quickly available to criminals so that flexibility of contra-measures, including development of deployable sensor networks, re-use of existing communication technologies with multi-mode operation, advanced signal processing is required to tackle the modern challenges. This requires targeted R&D of high-performance cost-effective electronic security (ESS) systems, including practical implementation and development of efficient digital signal processing algorithms. ESS is one of the world's largest (and growing) markets worth about $62 bn a year with UK companies fundamentally involved at the hi-tech end of this industry. An essential segment of the ESS market relates to perimeter/border protection solutions to provide situational awareness and, importantly, real-time recognition and identification of intruders, based on reliable all weather, day and night operation in complex environmental conditions. There is no single solution, so that general approach is to use all technologies and systems available, which can complement each other by providing additional information or data fusion. Widely used for surveillance, electro-optical or mm wave real time imaging systems are not efficient in the absence of line-of-sight and poor transparency of propagation media: walls, foliage, fog, smoke, snow, etc. In contrast, relatively low frequency radio signals penetrate such obstacles and this is the reason why all long-range surveillance and security missions are entrusted to radars. In traditional radar which process the reflections from the target, a target is viewed as a set of bright points, scintillating in amplitude and changing position with aspect angle, as it is composed of many scatterers. Thus even in high performance radar, automatic target recognition remains the most difficult task. At the same time the value of virtually all wide area surveillance radar is substantially reduced by the absence of reliable target classification functionality. This project addresses an important application area - that of low observable or, so-called 'difficult' target imaging in low-cost deployable radio frequency (RF) forward scatter (FS) perimeter protection radar networks. This radar has already proven its excellent detection and target parameter estimation ability. The highly sought-after recognition capability for such a radar network will be provided by combining, for the first time, the Target Shadow Profile Reconstruction (TSPR) technique with MIMO approaches. The novel imaging approach will be based on accurate solution of inverse diffraction problem to reconstruct the target silhouette by a network of distributed RF sensors, configured as a multi-tier chain of RF transmitters and receivers. Each pair of separated transmitter and receiver forms a section of an 'electronic fence', so that each crossing of the baseline is registered and processed in real time. A multi-tier configuration will provide crossings of multiple baselines by the same target allowing multi-perspective images, so that non-coherent MIMO will be exploited for enhanced imaging capability. Coherent synchronized virtual MIMO array will be also investigated on its ability to form an improved multi-perspective target shape outline. The reconstructed target profiles will be a base for the automatic target recognition (ATR).The introduction of target imaging by FS sensors will facilitate implementation of the fully functional radar system for perimeter protection and surveillance.