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This PhD thesis focuses on quantifying the impact of oscillator phase noise on the design of MMW CW radar systems with the goal of optimising the system to achieve better target detection and tracking. Phase noise in the transmitters of radar systems is known to distort the target response by broadening the linewidth and raising the noise floor of radar systems when a strong scatterer is present in the scene, hence degrading the detection and tracking performance. The situation is worse when multiple large scatterers are present, as the noise sidebands of all scatterers superimpose causing small targets, like pedestrians, to disappear in the phase noise sidebands. Some of the phase noise is cancelled at short ranges in coherent radars but the cancellation is not effective at long ranges. This research presents the design of phase noise reduction techniques. Phase noise modelling at the system level is presented to elaborate the methods of minimising the impact of phase noise. It will be shown that the frequency synthesiser is the most significant phase noise contributor. The design and implementation of a low phase noise signal source is presented. Both linear and non-linear phase noise models are used and developed further in order to meet the radar optimisation goals. An elaborate relationship of the phase spectrum with the RF spectrum of an oscillator is presented. The idea of coherence time is used as a tool for the selection of radar signal sources, and a novel derivation of the minimum bound on the transmitter phase noise level presented to prevent excessive distortion of target spectra. A new phase noise model is developed for the analog-to-digital conversion process using an independent sampling clock. The case of a sampling clock derived from the transmitter's reference oscillator will also be discussed. The models aid the selection of an appropriate sampling clock for a given radar application. A novel method of characterising the phase noise statistics using the integer and the fractional Brownian motion models will be presented. Models for the lineshape and the linewidth of the RF spectrum are dealt with in detail by reviewing the existing models in the literature. These analyses aid in assessing the fundamental resolution capability of radar systems in terms of the phase noise processes. A novel analysis of the RF spectrum of a signal impaired with random-walk phase noise is detailed, and it is shown that the RF spectrum exhibits time-dispersion and satellite peaks. It is shown that the success of the proposed work depends on techniques for careful measurement, analysis, and mitigation of the various noise processes.

The increasing penetration of low carbon technologies (LCTs) at customers’ premises, such as schools, homes and data centres, presents new opportunities for customers to take an active part in reducing energy and network costs through Demand Side Response (DSR). Meanwhile, the in depth DSR benefits on downstream network architecture, e.g. small and medium demand customers and distribution network operators, could be fully explored. Turning LCT into useful DSR resources to reduce energy volume or shift energy over time requires sophisticated control that can balance interests between customer, network and whole-sale energy market. The limitations of the current DSR control approaches are: 1) complex or inaccurate to formulate the increasingly complicated power flow brought by LCTs; 2) lack of interest balance between customers and network operators; 3) not able to facilitate customers in accessing to both local and central energy market. This research proposes a range of optimal DSR models in the low carbon environment to introduce three key innovations to overcome the limitation:1) a new problem formulation in DSR optimization model to maximize the customers’ DSR return. The proposed formulation generalizes the relationship between power and final energy cost as the simple piecewise functions. The enhanced formulation reduces optimization problem solving complexity and extends modelling capability for conversion efficiency in both local AC and DC low carbon network.2) a new Mixed Integer Linear Programming (MILP) based DSR optimization model that integrates the network demand reduction signal into the constraints of problem formulation to improve network operators’ benefit. This research also proposes a novel probability-based quantification method to assess the minimum DSR penetration for concrete network demand reduction considering the demand uncertainty.3) a new MILP based DSR trading model in the market environment of both local and central energy markets. Given different price signals, the proposed model determines the most profitable DSR trading behaviours for DSR providers across central and local energy markets.

A new method for implementing digital filters is discussed. The met11od maximises the output signal to noise ratio of a filter by assigning at each of the filter variables an optimal quantization law. A filter optimised for a gaussian process is considered in detail. An error model is developed and applied to first and second order canonic form filter sections. Comparisons are drawn between the gaussian optimised filter and the equivalent fixed point arithmetic filter. The performance of gaussian optimised filters under sinusoidal input signal conditions is considered ; it is found that the gaussian optimised filter exhibits a lower approximation error than the equivalent fixed point arithmetic filter. It is shown that when high order filters are implemented as a cascade of second order sections - with if necessary one first order section - the section ordering has a very small effect on the overall signal to noise r atio performance. A similar result for the pairing of poles and zeroes is found. Bounds on the maximum limit cycle amplitude for first and second order all-pole sections are presented. It is shown that for a first order all-pole the maximum limit cycle amplitude is lower than would be expected in the equivalent fixed point arithmetic filter, whereas , for the second order all- pole the bound is twice as large. Examples of a low-pass , band-pass and wideband differentiating filter,designed using free quantization law techniques,are presented. This new design method leads to a filter whose arithmetic operations can not be performed using fixed point arithmetic hardware. Instead, the filter must be represented as a finite state machine and then implemented using sequential logic circuit synthesis techniques. The logic complexity is found to depend - amongst other considerations - on the so called state (code) assignment. Some preliminary results on this problem are presented for the case of a next state function computed using the AND/EXCLUSIVE- OR (ring-sum) logic expansion. A review of the state assignment techniques in the literature is included. A part of the state assignment problem - for the case of AND/EX'·/OR logic - requires the numerous and consequently rapid computation of the Reed-Muller Transformation. A hardware processor - designed as an add-on to a minicomputer - is described; speed comparisons are drawn with the equivalent software algorithm.