http://hdl.handle.net/1842/3519 2013-06-12T10:18:21Z 2013-06-12T10:18:21Z Fotopoulou, Kyriaki http://hdl.handle.net/1842/6596 2013-03-28T16:10:38Z 2008-01-01T00:00:00Z

Title: Inductive Wireless Power Transfer for RFID & Embedded Devices: Coil Misalignment Analysis and Design Authors: Fotopoulou, Kyriaki Abstract: Radio frequency inductive coupling is extensively employed for wireless powering of embedded devices such as low power passive near-field RFID systems and implanted sensors. The efficiency of low power inductive links is typically less than 1%and is characterised by very unfavourable coupling conditions, which can vary significantly due to coil position and geometry. Although, a considerable volume of knowledge is available on this topic, most of the existing research is focused on the circuital modeling of the transformer action between the external and implanted coils. The practical issues of coil misalignment and orientation and their implications on transmission characteristics of RF links have been overlooked by researchers. The aim of this work is to present a novel analytical model for near-field inductive power transfer incorporating misalignment of the RF coil system. In this thesis the influence of coil orientation, position and geometry on the link efficiency is studied by approaching the problem from an electromagnetic perspective. In implanted devices some degree of misalignment is inevitable between external and implanted coils due to anatomical requirements. First two types of realistic misalignments are studied; a lateral displacement of the coils and an angular misalignment described as a tilt of the receiver coil. A loosely coupled system approximation is adopted since, for the coil dimensions and orientations envisaged, the mutual inductance between the transmitter and receiver coils can be neglected. Following this, formulae are derived for the magnetic field at the implanted coil when it is laterally and angularly misaligned from the external coil and a new power transfer function presented. The magnetic field solution is carried out for a number of practical antenna coil geometries currently popular in RFID and biomedical domains, such as planar and printed square, and circular spirals as well as conventional air-cored and ferromagnetic solenoids. In the second phase of this thesis, the results from the electromagnetic modeling are embodied in a near-field loosely coupled equivalent circuit for the inductive link. This allows us to introduce a power transfer formula incorporating for the first time coil characteristics and misalignment factors. This novel power transfer function allows a comparison between different coil structures such as short solenoids, with air or ferromagnetic core, planar and printed spirals with respect to power delivered at the receiver and its relative position to the transmitter. In the final stage of this work, the experimental verification of the model shows close agreement with the theoretical predictions. Using this analysis a formal design procedure is suggested that can be applied on a larger scale compared to existing methods. The main advantage of this technique is that it can be applied to a wide range of implementations without the limitations imposed by numerical modeling and existing circuital methods. Consequently, the designer has the flexibility to identify the optimum coil geometry for maximum power transfer and misalignment tolerance that suit the specifications of the application considered. This thesis concludes by suggesting a new optimisation technique for maximum power transfer with respect to read range, coil orientation, geometry and operating frequency. Finally, the limitations of this model are reiterated and possible future development of this research is discussed.

2008-01-01T00:00:00Z Ahiaga-Dagbui, Dominic D Smith, Simon D http://hdl.handle.net/1842/6550 2013-01-10T13:09:13Z 2012-09-01T00:00:00Z

Title: Neural networks for modelling the final target cost of water projects Authors: Ahiaga-Dagbui, Dominic D; Smith, Simon D Abstract: Producing reasonably accurate cost estimates at the planning stage of a project important for the subsequent success of the project. The estimator has to be able to make judgement on the cost influence of a number of factors including site conditions, procurement, risks, price changes, likely scope changes or type of contract. This can shroud the estimation process in uncertainty, which has often resulted in project cost overruns. The knowledge acquisition, generalization and forecasting capabilities of Artificial Neural Networks (ANN) are explored in this pilot study to build final cost estimation models that incorporate the cost effect of some of the factors mentioned above. Data was collected on ninety-eight water-related construction projects completed in Scotland between 2007-2011. Separate cost models were developed for normalized target cost and log of target costs. Variable transformation and weight decay regularization were then explored to improve the final model’s performance. As a prototype of a wider research, the final model’s performance was very satisfactory, demonstrating ANN ability to capture the interactions between the predictor variables and final cost. Ten input variables, all readily available or measurable at the planning stages for the project, were used within a Multilayer Perceptron Architecture and a Quasi-Newton training algorithm.

2012-09-01T00:00:00Z Ma, Junkang http://hdl.handle.net/1842/6497 2012-10-15T14:08:03Z 2010-06-28T00:00:00Z

Title: Ubiquitous communications for wireless personal area networks in a heterogeneous environment Authors: Ma, Junkang Abstract: The widespread use of wireless technologies has led to a tremendous development in wireless communication systems. Currently, an individual mobile user may carry multiple personal devices with multiple wireless interfaces, which can interconnect with each other to form a Wireless Personal Area Network (WPAN) which moves with this user. These devices exist in a heterogeneous environment which is composed of various wireless networks with differing coverage and access technologies and also the topology, device conditions and wireless connections in the WPAN may be dynamically changing. Such individual mobile users require ubiquitous communications anytime, anywhere, with any device and wish content to be efficiently and continuously transferred across the various wireless networks both outside and inside WPANs, wherever they move. This thesis presents research carried out into how to implement ubiquitous communications for WPANs in such an environment. Two main issues are considered. The first is how to initiate content transfer and keep it continuous, no matter which wireless network is used as a user moves or how the WPAN changes dynamically. The second is how to implement this transfer in the most efficient way: selecting the most suitable transfer mode for a WPAN according to the user’s and application’s requirements. User-centric (personal-area-centric) and contentcentric mechanisms are proposed in this thesis to address these issues. A scheme based on a Personal Distributed Environment (PDE) concept and designed as a logical user-based management entity is presented. This is based on three mechanisms which are proposed to overcome the technical problems in practical scenarios, which cannot be solved by existing approaches. A novel mechanism is proposed to combine local direct and global mobile communications, in order to implement ubiquitous communications in both infrastructure-less and infrastructurebased networks. This enables an individual user’s ubiquitous communications to be initiated in an infrastructure-less network environment and kept continuous when they move across infrastructure-based networks. Its advantages are evaluated by a performance analysis model and compared to existing solutions and verified by experiments. A cooperation and management scheme is also proposed for dynamic changes of multiple mobile routers and flexible switching of personal device roles in a WPAN while keeping ongoing ubiquitous communications continuous. This adopts a novel view of WPANs which solves the addressing problems caused by changes of mobile routers and makes these transparent to personal devices in the WPAN and external content sources. It provides an efficient method for changing the mobile router of a single WPAN or a WPAN merging with another moving network. Its benefits are demonstrated through performance analysis models. Finally, a novel user-centric and contentcentric mechanism for decision making, to select the most appropriate mobile router in a dynamically changing WPAN environment is proposed. This selects the most suitable content transfer mode for the WPAN to fulfil an individual user’s various requirements. It has different strategies to suit various types of applications. Selection results are demonstrated to verify the proposed mechanism in multiple scenarios of changing user requirements, applications and WPAN conditions.

2010-06-28T00:00:00Z Lim, Chin-Heng http://hdl.handle.net/1842/6373 2012-08-28T16:25:49Z 2006-01-01T00:00:00Z

Title: Bistatic Space-Time Adaptive Processing for Ground Moving Target Indication Authors: Lim, Chin-Heng Abstract: Space-time adaptive processing (STAP) for bistatic airborne radar offers several advantages, such as the higher possibility of detecting stealth targets. However, in a bistatic environment, the usual impediment and possible clutter in-homogeneity is further complicated by the rangedependent nature of the clutter ridge in the angle-Doppler plane induced by the physical geometry of the two aircrafts. This complicates the clutter suppression problem and leads to signi cant degradation in performance. The major objective of this thesis is to develop training methods for bistatic radar operation in a dense environment of ground-moving targets. The work is directed towards what may be called `small STAP', where the number of spatial channels is small and the array is non-uniform. The work is motivated by a desire to minimise the amount of navigational data associated with both the transmitter and receiver. Furthermore, it is directed towards environments where all range gates may contain targets. This thesis presents several novel STAP approaches, which can be classi ed into two main categories, to address the range dependency problem within a bistatic airborne radar framework. The rst category is on training strategies for joint-domain localised (JDL)-STAP in a bistatic environment. The JDL algorithm is originally proposed to reduce the computational complexity for monostatic radar by using a two-dimensional discrete Fourier transformation to transform the data from the space-time domain into the angle-Doppler domain. However, it has restrictions that essentially assume the receiving antenna to be an equi-spaced linear array of ideal, isotropic, point sensors. Two novel algorithms are proposed to overcome these two restrictions and they incorporate angle and Doppler compensation into the JDL processor to mitigate the bistatic clutter Doppler range dependency problem. In addition, a novel JDL in-the-gate processing approach is proposed, which forgoes the training data requirement and operates solely on the test data set. This single data set detection approach alleviates the high target density or heterogeneity problems associated with the training data requirement of conventional STAP algorithms. It is particularly applicable to heterogeneous environments where the clutter homogeneity assumption does not hold or independent training data is not readily available. The second category is on bistatic STAP training without navigation data. A novel technique is proposed to predict the range-dependent inverse covariance matrix, which is used to compute the STAP lter weights, by utilising linear prediction theory. The proposed technique provides mitigation against additional clutter notches resulting from range and Doppler ambiguities. It also allows for detection in other range gates under test without having to re-compute the prediction weights. Another novel technique is proposed to obtain an estimate of the rangedependent inverse covariance matrix by using an eigen-analysis based method. This technique involves applying eigen-decomposition to the covariance matrix in each range gate, sorting the eigenvalues by using maximum inner-product of the eigenvectors of the training range gate with respect to the test range gate and then averaging the resulting sorted eigenvalues. Both of the proposed techniques eliminate the requirement for a uniform linear array and can be applied to arrays of arbitrary con guration. No navigational data or parameter estimation is necessary as only the clutter data is required, thus reducing real-time computational costs.

2006-01-01T00:00:00Z