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Modern and future communication and radar systems require highly reconfigurable RF front-ends to realize the vision of Software-Defined Radio (SDR), where a single digitally-enabled radio is able to cover multiple bands and multiple operating standards. However, in the increasingly hostile RF environment, filtering becomes a bottleneck for SDRs as the traditional off-chip filters are fixed frequency and bulky. Therefore, tunable filtering is a critical building block for the reconfigurable RF front-ends and on-chip implementations are needed to meet size and weight constraints. On-chip passive components are lossy, especially inductors, and to fulfill the tunability requirements a number of active circuit techniques, e.g. N-path, Q-enhanced, discrete-time filters etc., have been developed. Most of these active filtering techniques, however, are limited to RF frequency range of few GHz and below. Additionally, these techniques lack or have very limited bandwidth tunability. On the other hand, Q-enhanced tunable LC filtering has the potential to be implemented at Microwave frequencies from 4~20 GHz and beyond. In this dissertation, a number of Q-enhanced parallel synthesis techniques have been proposed and implemented to achieve high-order, frequency tunable, and wide bandwidth tunable filters. First, a tunable 4th-order BPF was proposed and implemented in Silicon Germanium (SiGe) BiCMOS technology. Along with center frequency tuning, the filter achieves first ever reported 3-dB bandwidth tuning from 2% to 25%, representing 120 MHz to 1.5 GHz of bandwidth at 6 GHz. A new set of design equations were developed for the 4th-order parallel synthesis of BPF. A practical switched varactor control scheme is proposed for large tuning ratio varactors to reduce the nonlinear contribution from the varactor substantially which improves the tunable LC BPF filter linearity. Second, parallel addition and subtraction techniques were proposed to realize tunable dual-band filters. The subtraction technique is implemented in SiGe BiCMOS technology at X and Ku bands with more than 50 dB of out-of-band attenuation. Finally, a true wideband band-reject filter technique was proposed for microwave frequencies using parallel synthesis of two band-pass filters and an all-pass path. The proposed band-reject scheme is tunable and wide 20 dB attenuation bandwidths on the order of 10s of MHz to 100s of MHz can be achieved using this scheme. The implementation of the proposed parallel synthesis techniques in silicon technology along with measured results demonstrate that Q-enhanced filtering is favorable at higher microwave frequencies. Therefore, such implementations are suitable for future wireless communication and radar systems particularly wide bandwidth systems on the order of 100s of MHz to GHz. Future research includes, high-order reconfigurable band-pass and band-reject filters, automatic tuning control, and exploring the parallel synthesis techniques in Gallium Nitride (GaN) technology for high RF power applications. / PHD

Localization is an essential part of any autonomous vehicle. In a simple setting, the localization problem is almost trivial, and can be solved sufficiently using simple dead reckoning or an off-the-shelf GPS with differential corrections. However, as the surroundings become more complex, so does the localization problem. The urban environment is a prime example of a situation in which a vehicle's surroundings complicate the problem of position estimation. The urban setting is marked by tall structures, overpasses, and tunnels. Each of these can corrupt GPS satellite signals, or completely obscure them, making it impossible to rely on GPS alone. Dead reckoning is still a useful tool in this environment, but as is always the case, measurement and modeling errors inherent in dead reckoning systems will cause the position solution to drift as the vehicle travels eventually leading to a solution that is completely diverged from the true position of the vehicle. The most widely implemented method of combining the absolute and relative position measurements provided by GPS and dead reckoning sensors is the Extended Kalman Filter (EKF). The implementation discussed in this paper uses two Kalman Filters to track two completely separate position solutions. It uses GPS/INS and odometry to track the Absolute Position of the vehicle in the Global frame, and simultaneously uses odometry alone to compute the vehicle's position in an arbitrary Local frame. The vehicle is then able to use the Absolute position estimate to navigate on the global scale, i.e. navigate toward globally referenced checkpoints, and use the Relative position estimate to make local navigation decisions, i.e. navigating around obstacles and following lanes. This localization solution was used on team VictorTango's 2007 DARPA Urban Challenge entry, Odin. Odin successfully completed the Urban Challenge and placed third overall. / Master of Science

The doctoral thesis deals with development and design of novel architectures of digital filters for low-power integrated circuits. The main goal was to achieve optimum parameters of digital filters with respect to the chip area, power consumption and operating frequency. The target group of the proposed architectures are application specific integrated circuits designed for signal processing from sensors using delta-sigma modulators. Three novel architectures of digital filters optimized for low-power integrated circuits are presented in the thesis. The thesis provides analysis and comparison of parameters of the new filter architectures with the parameters of architectures generated by Matlab tool. A software tool has been designed and developed for the practical application of the proposed architectures of digital filters. The developed software tool allows generating hardware description of the filters with respect to defined parameters.

Small satellites are becoming increasingly appealing as technology advances and shrinks in both size and cost. The development time for a small satellite is also much less compared to a large satellite. For small satellites to be successful, the navigation systems must be accurate and very often they must be autonomous. For lunar navigation, contact with a ground station is not always available and the system needs to be robust. The extended Kalman filter is a nonlinear estimator that has been used on-board spacecraft for decades. The filter requires linear approximations of the state and measurement models. In the past few years, the unscented Kalman filter has become popular and has been shown to reduce estimation errors. Additionally, the Jacobian matrices do not need to be derived in the unscented Kalman filter implementation. The intent of this research is to explore the capabilities of the extended Kalman filter and the unscented Kalman filter for use as a navigation algorithm on small satellites. The filters are applied to a satellite orbiting the Moon equipped with an inertial measurement unit, a sun sensor, a star camera, and a GPS-like sensor. The position, velocity, and attitude of the spacecraft are estimated along with sensor biases for the IMU accelerometer, IMU gyroscope, sun sensor and star camera. The estimation errors are compared for the extended Kalman filter and the unscented Kalman filter for the position, velocity and attitude. The analysis confirms that both navigation algorithms provided accurate position, velocity and attitude. The IMU gyroscope bias was observable for both filters while only the IMU accelerometer bias was observable with the extended Kalman filter. The sun sensor biases and the star camera biases were unobservable. In general, the unscented Kalman filter performed better than the extended Kalman filter in providing position, velocity, and attitude estimates but requires more computation time. / text

An important aspect for precision guidance, navigation, and control for lunar operations is environmental modeling. In particular, consider gravity field modeling. Available gravity field models for the Moon reach degree and order 165 requiring the use and storage of approximately 26,000 spherical harmonic coefficients. Although the high degree and order provide a means by which to accurately predict trajectories within the influence of the Moon's gravitational field, the size of these models makes using them computationally expensive and restricts their use in design environments with limited computer memory and storage. It is desirable to determine reduced complexity realizations of the gravitational models to lower the computational burden while retaining the structure of the original gravitational field for use in rapid design environments. The extended Kalman filter and the unscented Kalman filter are used to create reduced order models and are compared against a simple truncation based reduction method. Both variations of the Kalman filter out perform the truncation based method as a means by which to reduce the complexity of the gravitational field. The extended Kalman filter and unscented Kalman filter were able to achieve good estimates of position while reducing the number of spherical harmonic coefficients used in gravitational acceleration calculations by approximately 5,400, greatly increasing the speed of the calculations while reducing the required computer allocation. / text

The objective of this research is to study various methods for censoring state estimate updates generated from radar measurements. The generated 2-D radar data are sent to a fusion center using the J-Divergence metric as the means to assess the quality of the data. Three different distributed sensor network architectures are considered which include different levels of feedback. The Extended Kalman Filter (EKF) and the Gaussian Particle Filter (GPF) were used in order to test the censoring methods in scenarios which vary in their degrees of non-linearity. A derivation for the direct calculation of the J-Divergence using a particle filter is provided. Results show that state estimate updates can be censored using the J-Divergence as a metric controlled via feedback, with higher J-Divergence thresholds leading to a larger covariance at the fusion center.

The ensemble Kalman filter (EnKF) is a reliable data assimilation tool for high-dimensional meteorological problems. On the other hand, the EnKF can be interpreted as a particle filter, and particle filters (PF) collapse in high-dimensional problems. We explain that these seemingly contradictory statements offer insights about how PF function in certain high-dimensional problems, and in particular support recent efforts in meteorology to 'localize' particle filters, i.e. to restrict the influence of an observation to its neighbourhood.

<p>Cake filtration is a unit operation to separate solids from fluids in industrial processes. The build up of a filter cake is usually accompanied with a decrease in overall permeability over the filter leading to an increased pressure drop over the filter. For an incompressible filter cake that builds up on a homogeneous filter cloth, a linear pressure drop profile over time is expected for a constant fluid volume flow. However, experiments show curved pressure drop profiles, which are also attributed to inhomogeneities of the filter (filter medium and/or residual filter cake).</p><p>In this work, a mathematical filter model is developed to describe the relationship between time and overall permeability. The model considers a filter with an inhomogeneous permeability and accounts for fluid mechanics by a one-dimensional formulation of Darcy's law and for the cake build up by solid continuity. The model can be solved analytically in the time domain. The analytic solution allows for the unambiguous inversion of the model to determine the inhomogeneous permeability from the time resolved overall permeability, e.g. pressure drop measurements. An error estimation of the method is provided by rewriting the model as convolution transformation.</p><p>This method is applied to simulated and experimental pressure drop data of gas filters with textile filter cloths and various situations with non-uniform flow situations in practical problems are explored. A routine is developed to generate characteristic filter cycles from semi-continuous filter plant operation. The model is modified to investigate the impact of non-uniform dust concentrations.</p>

In response to energy crisis and power quality concerns, three different methodologies to integrate the concept of active filtering into the alternators are proposed. Wind energy, due to its free availability and its clean and renewable character, ranks as the most promising renewable energy resource that could play a key role in solving the worldwide energy crisis. An Integrated Doubly-fed Electric Alternator/Active filter (IDEA) for wind energy conversion systems is proposed. The proposed IDEA is capable of simultaneous capturing maximum power of wind energy and improving power quality, which are achieved by canceling the most significant and troublesome harmonics of the utility grid and power factor correction and reactive power compensation in the grid. The back-to-back current regulated power converters are employed to excite the rotor of IDEA. The control strategy of rotor-side power converter is based on position sensoreless field oriented control method with higher power density. Analysis and experimental results are presented to demonstrate the effectiveness of the proposed IDEA. In next step, an integrated synchronous machine/active filter is discussed. The proposed technology is essentially a rotating synchronous machine with suitable modification to its field excitation circuit to allow dc and ac excitations. It is shown that by controlling the ac excitation, the 5th and 7th harmonics currents of the utility are compensated. The proposed method is cost effective because it can be applied to existing standby generators in commercial and industrial plants with minimal modification to the excitation circuits. To boost the gain of harmonic compensatory, an advanced electric machine is proposed. An Asymmetric Airgap Concentrated Winding Synchronous Machine (AACWSM) with ac and dc excitation was designed and employed. It is shown that the AACWSM with its unique design, in addition to power generation capability, could be used to compensate the most dominant current harmonics of the utility. The proposed AACWSM can compensate for the 5th and 7th harmonics currents in the grid by controlling the ac field excitation. In addition, the 11th and 13th harmonics currents are also significantly reduced. This system can be used at medium and low voltages for generation or motoring mode of operation.