Distributed unattended ground sensor (UGS) networks are commonly deployed to support wide area battlefield surveillance and monitoring missions. The information they generate has proven to be valuable in providing a necessary tactical information advantage for command and control, intelligence and reconnaissance field planning. Until recently, however, there has been greater emphasis within the defence research community for UGS networks to fulfil their mission objectives successfully, with minimal user interaction. For a distributed UGS scenario, this implies a network centric capability, where deployed UGS networks can self-manage their behaviour in response to dynamic environmental changes. In this thesis, we consider both the application interface and networking technologies required to achieve a network centric capability, within a distributed UGS surveillance setting. Three main areas of work are addressed towards achieving this. The first area of work focuses on a capability to support autonomous UGS network management for distributed surveillance operations. The network management aspect is framed in terms of how distributed sensors can collaborate to achieve their common mission objectives and at the same time, conserve their limited network resources. A situation awareness methodology is used, in order to enable sensors which have similar understanding towards a common objective to be utilised, for collaboration and to allow sensor resources to be managed as a direct relationship according to, the dynamics of a monitored threat. The second area of work focuses on the use of geographic routing to support distributed surveillance operations. Here we envisage the joint operation of unmanned air vehicles and UGS networks, working together to verify airborne threat observations. Aerial observations made in this way are typically restricted to a specific identified geographic area. Information queries sent to inquire about these observations can also be routed and restricted to using this geographic information. In this section, we present our bio-inspired geographic routing strategy, with an integrated topology control function to facilitate this. The third area of work focuses on channel aware packet forwarding. Distributed UGS networks typically operate in wireless environments, which can be unreliable for packet forwarding purposes. In this section, we develop a capability for UGS nodes to decide which packet forwarding links are reliable, in order to reduce packet transmission failures and improve overall distributed networking performance.

IT IS generally believed by the research community that the introduction of complex network functions—such as routing—in the optical domain will allow a better network utilisation, lower cost and footprint, and a more efficiency in energy usage. The new optical components and sub-systems intended for dynamic optical networking introduce new kinds of physical layer impairments in the optical signal, and it is of paramount importance to overcome this problem if dynamic optical networks should become a reality. Thus, the aim of this thesis was to first identify and characterise the physical layer impairments of dynamic optical networks, and then digital signal processing techniques were developed to mitigate them. The initial focus of this work was the design and characterisation of digital optical receivers for dynamic core optical networks. Digital receiver techniques allow for complex algorithms to be implemented in the digital domain, which usually outperform their analogue counterparts in performance and flexibility. An AC-coupled digital receiver for core networks—consisting of a standard PIN photodiode and a digitiser that takes samples at twice the Nyquist rate—was characterised in terms of both bit-error rate and packet-error rate, and it is shown that the packet-error rate can be optimised by appropriately setting the preamble length. Also, a realistic model of a digital receiver that includes the quantisation impairments was developed. Finally, the influence of the network load and the traffic sparsity on the packet-error rate performance of the receiver was investigated. Digital receiver technologies can be equally applied to optical access networks, which share many traits with dynamic core networks. A dual-rate digital receiver, capable of detecting optical packets at 10 and 1.25 Gb/s, was developed and characterised. The receiver dynamic range was extended by means of DC-coupling and non-linear signal clipping, and it is shown that the receiver performance is limited by digitiser noise for low received power and non-linear clipping for high received power.

Higher Order Neural Networks (HONNs) were introduced in the late 80's as a solution to the increasing complexity within Neural Networks (NNs). Similar to NNs HONNs excel at performing pattern recognition, classification, optimisation particularly for non-linear systems in varied applications such as communication channel equalisation, real time intelligent control, and intrusion detection. This research introduced new HONNs called the Generalised Correlation Higher Order Neural Networks which as an extension to the ordinary first order NNs and HONNs, based on interlinked arrays of correlators with known relationships, they provide the NN with a more extensive view by introducing interactions between the data as an input to the NN model. All studies included two data sets to generalise the applicability of the findings. The research investigated the performance of HONNs in the estimation of short term returns of two financial data sets, the FTSE 100 and NASDAQ. The new models were compared against several financial models and ordinary NNs. Two new HONNs, the Correlation HONN (C-HONN) and the Horizontal HONN (Horiz-HONN) outperformed all other models tested in terms of the Akaike Information Criterion (AIC). The new work also investigated HONNs for camera calibration and image mapping. HONNs were compared against NNs and standard analytical methods in terms of mapping performance for three cases; 3D-to-2D mapping, a hybrid model combining HONNs with an analytical model, and 2D-to-3D inverse mapping. This study considered 2 types of data, planar data and co-planar (cube) data. To our knowledge this is the first study comparing HONNs against NNs and analytical models for camera calibration. HONNs were able to transform the reference grid onto the correct camera coordinate and vice versa, an aspect that the standard analytical model fails to perform with the type of data used. HONN 3D-to-2D mapping had calibration error lower than the parametric model by up to 24% for plane data and 43% for cube data. The hybrid model also had lower calibration error than the parametric model by 12% for plane data and 34% for cube data. However, the hybrid model did not outperform the fully non-parametric models. Using HONNs for inverse mapping from 2D-to-3D outperformed NNs by up to 47% in the case of cube data mapping. This thesis is also concerned with the operation and training of NNs in limited precision specifically on Field Programmable Gate Arrays (FPGAs). Our findings demonstrate the feasibility of on-line, real-time, low-latency training on limited precision electronic hardware such as Digital Signal Processors (DSPs) and FPGAs. This thesis also investigated the effects of limited precision on the Back Propagation (BP) and Levenberg-Marquardt (LM) optimisation algorithms. Two new HONNs are compared against NNs for estimating the discrete XOR function and an optical waveguide sidewall roughness dataset in order to find the Minimum Precision for Lowest Error (MPLE) at which the training and operation are still possible. The new findings show that compared to NNs, HONNs require more precision to reach a similar performance level, and that the 2nd order LM algorithm requires at least 24 bits of precision. The final investigation implemented and demonstrated the LM algorithm on Field Programmable Gate Arrays (FPGAs) for the first time in our knowledge. It was used to train a Neural Network, and the estimation of camera calibration parameters. The LM algorithm approximated NN to model the XOR function in only 13 iterations from zero initial conditions with a speed-up in excess of 3 x 10^6 compared to an implementation in software. Camera calibration was also demonstrated on FPGAs; compared to the software implementation, the FPGA implementation led to an increase in the mean squared error and standard deviation of only 17.94% and 8.04% respectively, but the FPGA increased the calibration speed by a factor of 1:41 x 106.

Self-assembled III-V quantum dots (QDs) attract intense research interest and effort due to their unique physical properties arising from the three-dimensional confinement of carriers and discrete density of states. Semiconductor III-V QD laser structures exhibit dramatically improved device performance in comparison with their quantum well (QW) counterparts, notably their ultra low threshold current density, less sensitivity to defects and outstanding thermal stability. Therefore, integrating a high-quality QD laser structure onto silicon-based platform could potentially constitute a hybrid technology for the realization of optical inter-chip communications. This thesis is devoted to the development of high-performance InAs/GaAs QD lasers directly grown on silicon substrates and germanium substrates for silicon photonics. In the integration of III-V on silicon, direct GaAs heteroepitaxy on silicon is extremely challenging due to the substantial lattice and thermal expansion mismatch between GaAs and Si. The inherent high-density propagating dislocations can degrade the performance of III-V based lasers on silicon substrates. To enhance the device performance, QW dislocation filters are used here to create a strain field, which bends the propagating dislocations back towards the substrate. Here, we report the first operation of an electrically-pumped 1.3-\mu m InAs/GaAs QD laser epitaxially grown on Si (100) substrate. A threshold current density of 725 A/cm2 and an output power of 26 mW has been achieved for broad-area lasers with as-cleaved facets at room temperature. To avoid the formation of high-density threading dislocations (TDs), an alternative to direct growth of GaAs on silicon substrate is to use an intermediate material, which has a similar lattice constant to GaAs with fewer defects. Germanium appears to be the ideal candidate for a virtual substrate for GaAs growth, because germanium is almost lattice-matched to GaAs (only 0.08% mismatch). In the last 20 years, the fabrication of germanium-on-silicon (Ge/Si) virtual substrates has been intensely investigated with the demonstration of high-quality Ge/Si virtual substrates. The main challenge for the growth of GaAs on Ge/Si virtual substrate is to avoid the formation of anti-phase domains due to the polar/non-polar interface between GaAs and germanium. A new growth technique was invented for suppressing the formation of anti-phase domains for the growth of GaAs on germanium substrates at UCL. Based on this technique, lasing at a wavelength of 1305nm with a threshold current density of 55.2A/cm2 was observed for InAs/GaAs QD laser grown on germanium substrate under continuous-wave current drive at room temperature. The results suggest that long-wavelength InAs/GaAs QD lasers on silicon substrates can be realized by epitaxial growth on Ge/Si substrates. Studies in this thesis are an essential step towards the monolithic integration of long-wavelength InAs/GaAs QD lasers on a silicon substrate, as well as the integration of other III-V devices through fabricating III-V devices on silicon substrates.

Parallelism pervades the Internet, yet efficiently pooling this increasing path diversity has remained elusive. With no holistic solution for resource pooling, each layer of the Internet architecture attempts to balance traffic according to its own needs, potentially at the expense of others. From the edges, traffic is implicitly pooled over multiple paths by retrieving content from different sources. Within the network, traffic is explicitly balanced across multiple links through the use of traffic engineering. This work explores how the current architecture can be realigned to facilitate resource pooling at both network and transport layers, where tension between stakeholders is strongest. The central theme of this thesis is that traffic engineering can be performed more efficiently, flexibly and robustly through the use of re-feedback. A cross-layer architecture is proposed for sharing the responsibility for resource pooling across both hosts and network. Building on this framework, two novel forms of traffic management are evaluated. Efficient pooling of traffic across paths is achieved through the development of an in-network congestion balancer, which can function in the absence of multipath transport. Network and transport mechanisms are then designed and implemented to facilitate path fail-over, greatly improving resilience without requiring receiver side cooperation. These contributions are framed by a longitudinal measurement study which provides evidence for many of the design choices taken. A methodology for scalably recovering flow metrics from passive traces is developed which in turn is systematically applied to over five years of interdomain traffic data. The resulting findings challenge traditional assumptions on the preponderance of congestion control on resource sharing, with over half of all traffic being constrained by limits other than network capacity. All of the above represent concerted attempts to rethink and reassert traffic engineering in an Internet where competing solutions for resource pooling proliferate. By delegating responsibilities currently overloading the routing architecture towards hosts and re-engineering traffic management around the core strengths of the network, the proposed architectural changes allow the tussle surrounding resource pooling to be drawn out without compromising the scalability and evolvability of the Internet.

Liquid crystals (LC) are used in new applications of increasing complexity and smaller dimensions. This includes complicated electrode patterns and devices incorporating three dimensional geometric shapes, e.g. grating surfaces and colloidal dispersions. In these cases, defects in the liquid crystal director field often play an important part in the operation of the device. Modelling of these devices not only allows for a faster and cheaper means of optimising the design, but sometimes also provides information that would be difficult to obtain experimentally. As device dimensions shrink and complex geometries are introduced, one and two dimensional approximations become increasingly inaccurate. For this reason, a three dimensional finite element computer model for calculating the liquid crystal electro-hydrodynamics is programmed. The program uses the Q-tensor description allowing for variations in the liquid crystal order and is capable of accurately modelling defects in the director field. The aligning effect solid surfaces has on liquid crystals, known as anchoring, is essential to the operation of nearly all LC devices. A simplifying assumption often made in LC modelling is that of strong anchoring (the LC orientation is fixed at the LC- solid surface interface). However, in small scale structures with high electric fields and curved surfaces this assumption is often not accurate. A general expression that can be used to represent various weak anchoring types in the Landau-de Gennes theory is introduced. It is shown how experimentally measurable values can be assigned to the coefficients of the expression. Using the Q-tensor model incorporating the weak anchoring expression, the operation of the Post Aligned Bistable Nematic (PABN) device is modelled. Two stable states, one of higher and the other of lower director tilt angle, are identified. Then, the switching dynamics between these two states is simulated.

Bioelectrical impedance measurements are routinely used in many clinical applications such as lung function monitoring, brain imaging, body segment monitoring and tissue characterization. Advantages of the method include low-cost, simplicity and non-invasiveness. One bioimpedance imaging technique of particular interest is Electrical Impedance Tomography (EIT). EIT works by reconstructing the differences in electrical conductivity inside a body. The design of instrumentation for bioimpedance measurements is very challenging, particularly for applications requiring wideband operation (e.g., imaging of cancer biomarkers). Such applications require wideband current drivers that can deliver accurate and stable sinusoidal current (AC) to the electrode-tissue load. Many current drivers for bioimpedance measurements are based on discrete electronics, mostly using the modified Howland circuit (MHC). However, the accuracy and performance of the MHC depends on the performance of the operational amplifiers used and on the degree of matching of its resistors, making the approach not attractive for integration. In addition, because it uses both positive and negative feedback it can suffer from stability problems and since it employs voltage feedback it suffers from bandwidth limitations. This thesis is concerned with the design implementation and experimental evaluation of novel current drivers for wideband, fully-integrated, bioimpedance instrumentation for EIT applications. Three new current driver circuits are introduced based on the operational transconductance amplifier (OTA) approach, and implemented in sub-micron CMOS technology. The described integrated current drivers overcome many of the limitations of discrete current drivers, i.e., limited precision at high frequencies, stability, and low-bandwidth. Two new open-loop current drivers implemented in 0.35-μm CMOS technology are presented and their performance is analyzed and simulated. One of the current drivers was fabricated as an integrated circuit and its performance was experimentally verified using RC loads, a saline tank electrode phantom and electrodes on the forearm. In order to further improve its performance, a novel negative impedance converter (NIC) circuit is introduced which compensates for the stray capacitance at the output node due to the cable connecting the current driver to the electrodes. Finally, a new current driver in 0.6-μm CMOS technology is presented using feedback to provide high output impedance from DC to over1 MHz. Simulation results including Monte-Carlo analysis are presented to show the operation of the circuit.

Ground Moving Target Indication (GMTI) for radars with a small number of phase centres with low processing overhead is desirable for large scale deployment of unmanned aircraft (UAVs) in ground surveillance applications. Since there are often limitations associated with communication and onboard processing on UAVs, identifying moving targets from radar data gathered by these platforms for non-GMTI purposes would be an attractive prospect. The work presented here uses real radar data to assess the performance of the Displaced Phase Centre Antenna technique (DPCA), Adaptive DPCA and Joint Domain Localised Space Time Adaptive Processing on such data. It examines the influence of moving from two to three antenna elements and the performance of different processing configurations associated with a larger antenna array. Additionally, extended ground surveillance modes adopted by UAVs often involve a circular flightpath. In this case the DPCA condition is not met and so the GMTI performance is affected. This effect is investigated for both adaptive and non-adaptive signal processing algorithms on real data. The presence of internal clutter motion (ICM) in a scene and its influence on GMTI capability is also observed, using a synthesised clutter model. In pursuit of improving target detection performance while maintaining a relatively simple radar configuration, the use of a knowledge based approach to GMTI is discussed and a system is proposed that can provide rapid access to radar and image data while remaining robust and without limit on storage capacity. Finally the use of historical GMTI data from a common scene is proposed to increase the likelihood of identifying moving targets when using only basic GMTI processing. Experimental results are presented using real radar data, and optimal signal processing approaches are suggested for a variety of radar environments and hardware configurations.

The design of modern optical communication systems seeks a solution to the optimisation of bandwidth utilisation. Despite the inherent simplicity offered by intensity modulation direct detection (IM-DD), it is evident that this conventional binary scheme cannot fully explore in full the theoretical achievable capacity of optical systems. A lot of research activity is directing towards coherent detection techniques, already investigated in the early nineties, but then abandoned because of IM-DD cost efficiency and technological ease with erbium-doped fibre amplifiers. Coherent techniques require a more complex receiver architecture, but allow higher receiver sensitivity and more spectrally efficient modulation formats. With these advanced modulation formats it is possible to better exploit the wide bandwidth offered by the optical channel so that the total bit rate can be increased keeping affordable baud rates. Coherent detection is therefore a promising candidate that will most likely represent the future of optical communication systems. The aim of this thesis is to investigate coherent detection algorithms empowered by advanced digital signal processing (DSP) techniques for multilevel modulation formats to improve the performance of coherent systems. We first review the basic concepts of coherent detection. Algorithms for the compensation of imperfections in the receiver front-end are investigated. Characterisation of time-interleaved ADCs is presented and it is shown that the imperfections can be mitigated using DSP. The digital compensation of quadrature imbalance due to imperfections in a digital coherent receiver is then discussed. Blind equalisation techniques for the 16-QAM modulation format are also presented. Next, algorithms to compensate for frequency offset and laser phase noise for a 16-QAM coherent system are discussed. We consider a second-order recursive digital loop to track frequency offset from the transmitter laser and the LO. Finally, the thesis examines the interaction between the LO phase noise and electronically-compensated chromatic dispersion.

In the last decade the new scientific field of Lab-On-a-Chip (LOAC) systems arose. This field focuses on the miniaturization of standard and new laboratory techniques responsible for the manipulation and detection of biomolecules. This is a very diverse field with a vast number of different techniques being employed in order to develop such systems. The work carried out, focused on the detection of biomolecules. Electrochemical Impedance Spectroscopy (EIS), where the impedance is being measured as a function of frequency, has been used for the last 20 years in biosensor applications. However, it has failed to become widely available. The wider interest has been in the experimental procedure and not the instrumentation required or more importantly, the optimization of the electrode system used. Development of a customized system for the specific application and integration of such an instrument on a single microchip, would greatly aid towards the development, widespread deployment and standardization of EIS as a competitive, accurate, portable, simple to use, low cost, fast and label-free detection technique. This project, focused on the development of a tetrapolar impedance system, as tetrapolar electrode systems offer the advantage of reduced interfacial electrode polarization in contrast to bipolar and tripolar systems. For proof of principle, EIS was applied in the analysis of a biosensor developed for the detection of hCGb, a protein associated with various types of cancer. Commercially available coplanar-microband gold-electrode arrays were used in conjunction with a commercial impedance analyser in order to perform this analysis. Preliminary results indicated a clear differentiation between different biological and chemical layers and more importantly indicated hCGb detection. Thus, applicability of the tetrapolar technique for biomolecule detection was illustrated. The commercial electrode array, even though it did provide positive and promising results, was not optimized for the specific application. In order to do so, the Finite Element Method (FEM) modelling technique (Comsol Multiphysics) was employed in order to investigate the electric field properties of tetrapolar sensors. By utilizing the Geselowitz sensitivity theorem, the dependence of the sensitivity of the sensor to impedance changes on the sensor geometry was examined and understood. In order to optimize the sensor, a dedicated Matlab code employing the Conformal Mapping (CM) technique, was developed. This allowed the examination of the response of the sensitivity function over a specific region for millions of different geometries, reducing the computational and analytical time required with FEM. With 2D and 3D FEM models agreeing with the CM results and thus validating the CM analysis, a number of optimized tetrapolar sensors were generated. The optimization free parameters were the width (W) and the distance (D) between pairs of electrodes. The results also proved to be able to be scaled up and thus, a scaled-up (by 5x105) tank model of one of the optimized sensors was developed in order to experimentally prove the analysis. The first step towards a tetrapolar system is the bipolar and consequently bipolar (and thus interdigital) electrode systems were also briefly examined.