Browsing by Subject "Estimation"
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Item A Methodology for Estimating Construction Unit Bid Prices(2012-11-28) Erbatur, Osman 1978-The internship company does not have a standard procedure for preparing an engineer?s estimate of probable construction cost document (engineer?s estimate) for municipal projects. Every project manager employs a methodology that is a slightly different variation of the historical data approach. The internship objective was to develop a construction unit price estimation model that provides more accurate results than the company?s existing unit price estimation methodology for the City of Fort Worth construction projects. To accomplish the internship objective several tasks were conducted, including; gathering City of Fort Worth construction projects bid tabulation data (including all bids) for the past three years; developing three construction item unit price databases using the data collected; conducting statistical analyses using the unit price databases;developing tables and graphs showing the construction cost items and their appropriate estimated unit prices to be used by the project managers in their cost estimates; developing an approach to apply construction unit costs which adjusts for unique project characteristics; developing guidelines for using the developed tables and graphs to estimate unit prices for municipal projects; using one recent project to compare the company?s existing unit price estimation methodology and the new developed model with actual unit bid prices; and developing guidelines for updating the unit price database, tables, and graphs. The study made use of both normal and log-normal distributions to model the unit bid price data collected from the City of Fort Worth. The factors that are perceived to influence a contractor?s unit bid price for a given item were identified and given a degree of impact on the project by the project managers. The factor that had the highest impact on the unit bid prices was discovered to be item quantity. The unit price estimating methodology presented in this study generated a better fit than the internship company?s original method for predicting the actual average unit bid prices for the one case study the methodology was applied.Item Analysis and synthesis of collaborative opportunistic navigation systems(2014-05) Kassas, Zaher; Humphreys, Todd Edwin; Arapostathis, Ari, 1954-Navigation is an invisible utility that is often taken for granted with considerable societal and economic impacts. Not only is navigation essential to our modern life, but the more it advances, the more possibilities are created. Navigation is at the heart of three emerging fields: autonomous vehicles, location-based services, and intelligent transportation systems. Global navigation satellite systems (GNSS) are insufficient for reliable anytime, anywhere navigation, particularly indoors, in deep urban canyons, and in environments under malicious attacks (e.g., jamming and spoofing). The conventional approach to overcome the limitations of GNSS-based navigation is to couple GNSS receivers with dead reckoning sensors. A new paradigm, termed opportunistic navigation (OpNav), is emerging. OpNav is analogous to how living creatures naturally navigate: by learning their environment. OpNav aims to exploit the plenitude of ambient radio frequency signals of opportunity (SOPs) in the environment. OpNav radio receivers, which may be handheld or vehicle-mounted, continuously search for opportune signals from which to draw position and timing information, employing on-the-fly signal characterization as necessary. In collaborative opportunistic navigation (COpNav), multiple receivers share information to construct and continuously refine a global signal landscape. For the sake of motivation, consider the following problem. A number of receivers with no a priori knowledge about their own states are dropped in an environment comprising multiple unknown terrestrial SOPs. The receivers draw pseudorange observations from the SOPs. The receivers' objective is to build a high-fidelity signal landscape map of the environment within which they localize themselves in space and time. We then ask: (i) Under what conditions is the environment fully observable? (ii) In cases where the environment is not fully observable, what are the observable states? (iii) How would receiver-controlled maneuvers affect observability? (iv) What is the degree of observability of the various states in the environment? (v) What motion planning strategy should the receivers employ for optimal information gathering? (vi) How effective are receding horizon strategies over greedy for receiver trajectory optimization, and what are their limitations? (vii) What level of collaboration between the receivers achieves a minimal price of anarchy? This dissertation addresses these fundamental questions and validates the theoretical conclusions numerically and experimentally.Item An attitude determination and control system for small satellites(2015-05) Tam, Margaret Hoi Ting; Fowler, Wallace T.; Lightsey, E. GlennA flexible, robust attitude determination and control (ADC) system is presented for small satellite platforms. Using commercial-off-the-shelf sensors, reaction wheels, and magnetorquers which fit within the 3U CubeSat form factor, the system delivers arc-minute pointing precision. The ADC system includes a multiplicative extended Kalman filter for attitude determination and a slew rate controller that acquires a view of the Sun for navigation purposes. A pointing system is developed that includes a choice of two pointing controllers -- a proportional derivative controller and a nonlinear sliding mode controller. This system can reorient the spacecraft to satisfy a variety of mission objectives, but it does not enforce attitude constraints. A constrained attitude guidance system that can enforce an arbitrary set of attitude constraints is then proposed as an improvement upon the unconstrained pointing system. The momentum stored by the reaction wheels is managed using magnetorquers to prevent wheel saturation. The system was thoroughly tested in realistic software- and hardware-in-the-loop simulations that included environmental disturbances, parameter uncertainty, actuator dynamics, and sensor bias and noise.Item Conservative estimation of overvoltage-based PV hosting capacity(2014-08) Jonsson, David Orn; Santoso, SuryaThe primary objective of this work is to develop and demonstrate a steady-state stochastic simulation method to estimate the PV hosting capacity of a given distribution, based on the ANSI voltage regulation standard. The work discusses the key factors that determine the voltage rise due to distributed PV. Load demand analysis is done to determine statistically representative minimum daylight load demand for PV analysis. And lastly, the steady-state, stochastic simulation method is discussed and implemented to estimate the PV hosting capacity for small-scale and large-scale PV Deployments.Item Development of Diagnostic Algorithms for Air Brakes in Trucks(2011-10-21) Dhar, SandeepIn this dissertation, we focus on development of algorithms for estimating the severity of air leakage and for predicting the out-of-adjustment of pushrod in an air brake system of heavy commercial vehicles. The leakage of air from the brake system causes a reduction in the steady-state pressure in the brake chamber and an increase in the lag of the braking pressure response thereby increasing the stopping distance of the vehicle. Currently a presence of leak in the system is detected for the severities of leak that cause the reservoir pressure to drop below a threshold, such as, the leakage of compressed air due to rupture of the reservoir or of the hoses carrying the compressed air. The leakage of air is also possible due to several other reasons such as, cracks in the hoses, loose couplings between the hoses etc. The severities of leak, corresponding to such situations, do not lead to the reservoir pressure drop below the threshold; therefore, their presence remains undetected. For the detection and estimation of such severities of leak, a diagnostic scheme has been given and is based on a model developed for the mass ow rate of the leakage of air from the air brake system. Out-of-adjustment of the pushrod is the extension of pushrod beyond a prede- ned value and for safety concerns, an extension beyond this value is not desired. Currently no warning system is available for monitoring the out-of-adjustment of pushrod, except, during the safety inspection. Inspection of the pushrod for outof- adjustment is the most labor-intensive and time consuming task during a typical safety inspection procedure. For efficient and continuous monitoring of the pushrod for out-of-adjustment, a diagnostic algorithm for estimating the steady-state pushrod stroke has been developed. The scheme is expected to expedite the inspection process for the out-of-adjustment of pushrod. Experimental data from the air brake test setup at Texas A and M University has been used for corroborating both the models. Also, the problem of parameter estimation of sequential hybrid systems such as the air brake system, has been addressed. The \hybrid" nature of the air brake system stems from the system being in di erent modes corresponding to di erent values of the displacement of the pushrod and is a result of di erent spring compliances associated with the pushrod in di erent ranges of its displacement. The air brake system is \sequential" in the sense that as the pressure increases, the displacement of the pushrod increases and there is a distinct sequence of modes that the system will transition through and upon a reduction in pressure, the sequence of modes is revisited in the reverse order. The mode to mode transition of the air brake system is governed by the parameters, such as, the clearance between the brake pad and the brake drum. The problem of estimation, that has been addressed, is as follows: Suppose the pressure in the air brake system were to be measured and that the motion of the pushrod is not measured. Is it possible to estimate the nal displacement of the pushrod without knowing the parameters, such as the clearance, that govern the system to transition from one mode to another?Item Distributed Linear Combination Estimators for Localization Based on Received Signal Strength(2013-12-05) Chen, Wei-YuLocating the position of a radio frequency device is indispensable in many wireless applications. The most famous method is the Global Positioning System (GPS), which uses trilateration with satellites, is generally unavailable for indoor devices and expensive for large networks. Therefore, this dissertation aims to develop and discuss accurate, fast, low-cost, energy-efficient, and robust localization algorithms especially based on the received signal strength (RSS). This dissertation proposes a distributed and iterative estimator by linearly combining location estimates from maximum likelihood based range estimates. In non- cooperative cases where unknown-location (blindfolded) devices only utilize the in- formation from known-location devices (anchors), each combining weight is proportional to the reciprocal of the estimated distance squared between the blindfolded node and an anchor. The numerical simulations demonstrate that the proposed LC estimator has similar error behaviors to the maximum likelihood estimator (MLE) and fewer computations under various topologies and noisy wireless environments. If the parameters for the RSS model are unknown, they are estimated by the least square and/or maximum likelihood methods. The accuracy difference of the linear combination estimators by estimated and perfect parameters is acceptable and decreasing as more anchors are deployed. In cooperative localization, a blindfolded node uses information from not only anchors but also other blindfolded nodes. The combining weight is now proportional to the reciprocal of the estimated distance squared and the transmitter?s positioning error. After being mainly compared with the distributed maximum likelihood estimator by coordinate descent method and the distributed weighted-multidimensional scaling (dwMDS) method, the LC estimator performs well in accuracy, computation time, and the use of wireless transmissions under various topologies, connectivities, and noisy environments. Moreover, the estimation error is clipped by upper and lower bounds. The drawback is that the convergence is not guaranteed, although non-convergent cases rarely happen. For the connectivity issue, placing more nodes with smaller transmitting ranges results in fewer connected nodes and less power consumption. However, to improve localization of an existing system, the relative costs of node and consumed power must be considered to determine the lowest cost system. Finally, the density of blindfolded nodes is two to three times to the density of anchors to achieve the same accuracy.Item Estimation Strategies for Constrained and Hybrid Dynamical Systems(2012-10-19) Parish, Julie Marie JonesThe estimation approaches examined in this dissertation focus on manipulating system dynamical models to allow the well-known form of the continuous-discrete extended Kalman filter (CDEKF) to accommodate constrained and hybrid systems. This estimation algorithm filters sequential discrete measurements for nonlinear continuous systems modeled with ordinary differential equations. The aim of the research is to broaden the class of systems for which this common tool can be easily applied. Equality constraints, holonomic or nonholonomic, or both, are commonly found in the system dynamics for vehicles, spacecraft, and robotics. These systems are frequently modeled with differential algebraic equations. In this dissertation, three tools for adapting the dynamics of constrained systems for implementation in the CDEKF are presented. These strategies address (1) constrained systems with quasivelocities, (2) kinematically constrained redundant coordinate systems, and (3) systems for which an equality constraint can be broken. The direct linearization work for constrained systems modeled with quasi-velocities is demonstrated to be particularly useful for systems subject to nonholonomic constraints. Concerning redundant coordinate systems, the "constraint force" perspective is shown to be an effective approximation for facilitating implementation of the CDEKF while providing similar performance to that of the fully developed estimation scheme. For systems subject to constraint violation, constraint monitoring methods are presented that allow the CDEKF to autonomously switch between constrained and unconstrained models. The efficacy of each of these approaches is shown through illustrative examples. Hybrid dynamical systems are those modeled with both finite- and infinite-dimensional coordinates. The associated governing equations are integro-partial differential equations. As with constrained systems, these governing equations must be transformed in order to employ the CDEKF. Here, this transformation is accomplished through two finite-dimensional representations of the infinite-dimensional coordinate. The application of these two assumed modes methods to hybrid dynamical systems is outlined, and the performance of the approaches within the CDEKF are compared. Initial simulation results indicate that a quadratic assumed modes approach is more advantageous than a linear assumed modes approach for implementation in the CDEKF. The dissertation concludes with a direct estimation methodology that constructs the Kalman filter directly from the system kinematics, potential energy, and measurement model. This derivation provides a straightforward method for building the CDEKF for discrete systems and relates these direct estimation ideas to the other work presented throughout the dissertation. Together, this collection of estimation strategies provides methods for expanding the class of systems for which a proven, well-known estimation algorithm, the extended Kalman filter, can be applied. The accompanying illustrative examples and simulation results demonstrate the utility of the methods proposed herein.Item Evaluation and extension of threaded control for high-mix semiconductor manufacturing(2010-12) Patwardhan, Ninad Narendra; Flake, Robert H.; Edgar, Thomas F.In the recent years threaded run-to-run (RtR) control algorithms have experienced drawbacks under certain circumstances, one such trait is when applied to high-mix of products such as in Application Specific Integrated Circuits (ASIC) foundries. The variations in the process are a function of the product being manufactured as well as the tool being used. The presence of semiconductor layers increases the number of times the lithography process must be repeated. Successive layers having different patterns must be exposed using different reticles/masks in order to maximize tool utilizations. The objectives of this research are to develop a set of methodologies for evaluation and extension of threaded control applied to overlay. This project defines methods to quantify the efficacy of threaded controls, finds the drawbacks of threaded control under production of high mix of semiconductors and suggests extensions and alternatives to improve threaded control. To evaluate the performance of threaded control, extensive simulations were performed in MATLAB. The effects of noise, disturbances, sampling and delays on the control and estimation performance of threaded controller were studied through these simulations. Based on the results obtained, several ideas to extend threaded control by reducing overall number of threads, by improving thread definitions and combination have been introduced. A unique idea of sampling the measurements dynamically based on the estimation accuracy is also presented. Future work includes implementing the extensions to threaded control suggested in this work in real production data and comparing the results without the use of those methods. Future work also includes building new alternatives to threaded control.Item Experimental Investigation of Helicopter Weight and Mass Center Estimation(2013-04-09) Taylor, Bradley WhittenReal-time estimates of weight and mass center location for helicopters are desirable for flight control and condition-based maintenance purposes. While methods to estimate mass parameters of helicopters have been developed, they often assume near-perfect knowledge of helicopter dynamics and have been validated only through simulated measurement data. The work described here aims to experimentally validate a method for weight and mass center estimation using an ALIGN T-REX 600e R/C helicopter. The estimation algorithm utilizes an extended Kalman filter (EKF) which estimates the helicopter states along with the weight and mass center location in real-time. Nonlinear system identification is performed using maximum likelihood estimation to create an accurate dynamic model for use in the EKF. Results show that given a reasonably accurate dynamic model, weight, stationline mass center location, and buttline mass center location can be reliably estimated in non-descending flight conditions. Weight estimation is shown to be robust to sudden weight changes during flight, whereas stationline and buttline mass center estimates are marginally robust to sudden shifts in the mass center location. Waterline mass center proved to be unobservable for the axial flight maneuvers conducted. Detailed flight test studies characterize estimation error in weight and three-dimensional mass center position using the EKF formulation.Item Facility planning and value of information using a tank reservoir model : a case study in reserve uncertainty(2010-05) Singh, Ashutosh; Jablonowski, Christopher J.; Groat, Charles G.This thesis presents a methodology to incorporate reservoir uncertainties and estimate the loss in project value when facility planning decisions are based on erroneous estimates of input variables. We propose a tank model along with integrated asset development model to simulate the concept selection process. The model endogenizes drilling decisions and includes an option to expand. Key decision variables included in the model are number of pre-drill wells, initial facility capacity and number of well slots. Comparison is made between project value derived under erroneous estimates for reserve size and under an alternate hypothesis. The results suggest loss in project value of up to 40% when reservoir estimates are erroneous. Moreover, both optimistic and pessimistic reserve estimates results in a loss in project value. However, loss in project value is bigger when reserve size is underestimated than when it is overestimated.Item Integrated performance prediction and quality control in manufacturing systems(2014-12) Bleakie, Alexander Q.; Djurdjanovic, DraganPredicting the condition of a degrading dynamic system is critical for implementing successful control and designing the optimal operation and maintenance strategies throughout the lifetime of the system. In many situations, especially in manufacturing, systems experience multiple degradation cycles, failures, and maintenance events throughout their lifetimes. In such cases, historical records of sensor readings observed during the lifecycle of a machine can yield vital information about degradation patterns of the monitored machine, which can be used to formulate dynamic models for predicting its future performance. Besides the ability to predict equipment failures, another major component of cost effective and high-throughput manufacturing is tight control of product quality. Quality control is assured by taking periodic measurements of the products at various stages of production. Nevertheless, quality measurements of the product require time and are often executed on costly measurement equipment, which increases the cost of manufacturing and slows down production. One possible way to remedy this situation is to utilize the inherent link between the manufacturing equipment condition, mirrored in the readings of sensors mounted on that machine, and the quality of products coming out of it. The concept of Virtual Metrology (VM) addresses the quality control problem by using data-driven models that relate the product quality to the equipment sensors, enabling continuous estimation of the quality characteristics of the product, even when physical measurements of product quality are not available. VM can thus bring significant production benefits, including improved process control, reduced quality losses and higher productivity. In this dissertation, new methods are formulated that will combine long-term performance prediction of sensory signatures from a degrading manufacturing machine with VM quality estimation, which enables integration of predictive condition monitoring (prediction of sensory signatures) with predictive manufacturing process control (predictive VM model). The recently developed algorithm for prediction of sensory signatures is capable of predicting the system condition by comparing the similarity of the most recent performance signatures with the known degradation patterns available in the historical records. The method accomplishes the prediction of non-Gaussian and non-stationary time-series of relevant performance signatures with analytical tractability, which enables calculations of predicted signature distributions with significantly greater speeds than what can be found in literature. VM quality estimation is implemented using the recently introduced growing structure multiple model system paradigm (GSMMS), based on the use of local linear dynamic models. The concept of local models enables representation of complex, non-linear dependencies with non-Gaussian and non-stationary noise characteristics, using a locally tractable model representation. Localized modeling enables a VM that can detect situations when the VM model is not adequate and needs to be improved, which is one of the main challenges in VM. Finally, uncertainty propagation with Monte Carlo simulation is pursued in order to propagate the predicted distributions of equipment signatures through the VM model to enable prediction of distributions of the quality variables using the readily available sensor readings streaming from the monitored manufacturing machine. The newly developed methods are applied to long-term production data coming from an industrial plasma-enhanced chemical vapor deposition (PECVD) tool operating in a major semiconductor manufacturing fab.Item Modeling, estimation, and control of proton exchange membrane-based electrochemical systems(2015-12) Yu, Victor Kin-Wah; Chen, Dongmei, Ph. D.; Longoria, Raul G; Deshpande, Ashish D; Fahrenthold, Eric P; Edgar, Thomas FTo reduce emissions and meet the rapidly growing global energy demand, affordable and efficient methods of electrical energy storage and generation are needed to exploit renewable energy sources more effectively. Proton exchange membrane (PEM) based electrochemical systems, such as vanadium redox flow batteries (VRFB) and PEM fuel cells, are playing an increasingly important role because they have a fast response rate, high efficiency, and small environmental impact. However, widespread commercial viability of these technologies in the future heavily depends on further improvements in their performance and reliability. Accordingly, this dissertation focuses on developing new methodologies to predict and control the behavior of these PEM-based electrochemical systems. In the first part of this work, a control-oriented physics-based model of a VRFB system is developed. This model can predict the transient response of the cell voltage under different operating conditions and inputs such as current, flow rate, and temperature. The significance of this study is having the ability to predict the short and long term effects of membrane crossover on the system performance. One major challenge of operating VRFB systems is that monitoring the state-of-charge (SOC) in real-time using traditional measurement techniques is expensive and impractical. To address this problem, an SOC estimator is developed based on a constrained extended Kalman filter that can be used for real-time optimization and control because it requires only simple voltage measurements and a low-order model. Simulation results demonstrate the ability to predict the vanadium concentrations of a VRFB system without knowledge of the crossover dynamics. A major obstacle preventing the widespread commercialization of VRFBs is excessive capital costs. This issue is addressed by developing a methodology to optimally size a VRFB system using the minimum amount of materials required for the intended power range. For PEM fuel cells, proper water and thermal management is critical to optimizing performance and longevity. However, this can be a challenging task due to strong system interactions between multiple input and output variables. In the final part of this work, these system interactions are studied in detail and a suitable controller is designed to regulate the stack voltage, stack temperature, and relative humidity during load transients.Item Parameter estimation in ordinary differential equations(Texas A&M University, 2004-09-30) Ng, Chee LoongThe parameter estimation problem or the inverse problem of ordinary differential equations is prevalent in many process models in chemistry, molecular biology, control system design and many other engineering applications. It concerns the re-construction of auxillary parameters by fitting the solution from the system of ordinary differential equations( from a known mathematical model) to that of measured data obtained from observing the solution trajectory. Some of the traditional techniques (for example, initial value technques, multiple shooting, etc.) used to solve this class of problem have been discussed. A new algorithm, motivated by algorithms proposed by Childs and Osborne(1996) and Z.F.Li's dissertation(2000), has been proposed. The new algorithm inherited the advantages exhibited in the above-mentioned algorithms and, most importantly, the parameters can be transformed to a form that are convenient and suitable for computation. A statistical analysis has also been developed and applied to examples. The statistical analysis yields indications of the tolerance of the estimates and consistency of the observations used.Item Phase Retrieval Using Estimation Methods For Intensity Correlation Imaging(2010-10-12) Young, Brian T.The angular resolution of an imaging system is sharply bounded by the diffraction limit, a fundamental property of electromagnetic radiation propagation. In order to increase resolution and see finer details of remote objects, the sizes of telescopes and cameras must be increased. As the size of the optics increase, practical problems and costs increase rapidly, making sparse aperture systems attractive for some cases. The method of Intensity Correlation Imaging (ICI) provides an alternative method of achieving high angular resolution that allows a system to be built with less stringent precision requirements, trading the mechanical complexity of a typical sparse aperture for increased computational requirements. Development of ICI has stagnated in the past due to the inadequacies of computational capabilities, but the continued development of computer technologies now allow us to approach the image reconstruction process in a new, more e ffctive manner. This thesis uses estimation methodology and the concept of transverse phase diversity to explore the modern bounds on the uses of ICI. Considering astronomical observations, the work moves beyond the traditional, single-parameter uses of ICI, and studies systems with many parameters and complex interactions. It is shown that ICI could allow significant new understanding of complex multi-star systems. Also considered are exoplanet and star-spot measurements; these are less promising due to noise considerations. Looking at the Earth imaging problem, we find significant challenges, particularly related to pointing requirements and the need for a large field-of-view. However, applying transverse phase diversity (TPD) measurements and a least-squares estimation methodology solves many of these problems and re-opens the possibility of applying ICI to the Earth-imaging problem. The thesis presents the TPD concept, demonstrates a sample design that takes advantage of the new development, and implements reconstruction techniques. While computational challenges remain, the concept is shown to be viable. Ultimately the work presented demonstrates that modern developments greatly enhance the potential of ICI. However, challenges remain, particularly those related to noise levels.Item Real-time estimation of MIG welding weld bead width using an IR camera(2009-08) Casey, Patrick John; Beaman, Joseph J.; Bourell, DavidCurrent manufacturing process controls are principally based only on statistical performance. The next evolution is to make physics based models combined with the state of the art sensors and actuators to control the manufacturing processes. In this paper, metal inert gas welding is used as an example of how the first steps in developing a reliable estimation technique to implement a physics based controller. The weld bead geometry will be the main focus because it is crucial to creating a quality weld. This paper uses an IR camera to generate and evaluate multiple weld bead width estimation techniques and characterizes their corresponding standard deviations. Also a Gaussian Mixture Model (GMM) is used to fit the temperature linescan data to fit an analytical function to the numerical data. The GMM is then used to estimate the weld bead width. Finally, the optimal linescan location is calculated to produce the best possible weld bead estimation. The result is that only one of the estimation techniques actually follows a step input and vi the optimal linescan location is 4 mm from the back of the arc. Furthermore, the GMM provides an excellent fit to the temperature linescan, but does not increase the accuracy of the estimate.Item Sensitivity analysis of repeat track estimation techniques for detection of elevation change in polar ice sheets(2010-05) Harpold, Robert Earl; Schutz, Bob E.; Urban, Timothy J.; Catania, Ginny; Fowler, Wallace; Ocampo, CesarRepeat track analysis is one tool that can be used to derive parameters describing elevation changes from elevation data collected from a satellite with a near-repeat groundtrack. While initially developed to study ocean topography, it was then applied to ice sheet data. This study expands upon that previous research by testing the method’s ability to estimate parameters using different amounts of data, different grid sizes and types, and different elevation models containing different parameters to be estimated. In all cases, ICESat-derived elevations were used as input data, as ICESat has a near-repeat groundtrack with extensive coverage of the Greenland and Antarctica ice sheets. Results were compared using the differences between modeled and ICESat-derived elevations, correlation of estimated parameters to known physical features, and differences between known and estimated parameter values for simulated elevation data. It was found that there should be data from at least as many distinct time periods (or, in the case of ICESat, laser campaigns) as parameters being estimated, grids centered on and aligned with the reference groundtrack should be used, and that elevation models containing a constant elevation change rate, slopes, an initial elevation at the grid center, and annual terms should be used. Crossover analysis is a different method to determine elevation change rate with elevation data and serves as an independent verification of the repeat track analysis method. It was found that the hdot values determined from crossover and repeat track analyses agreed to within 5 cm/yr in most areas of the ice sheets, with differences greater than 40 cm/yr along the coasts. While repeat track analysis provides greater coverage than crossover analysis, it is uncertain which method provides the most accurate results.Item Single station Doppler tracking for satellite orbit prediction and propagation(2015-05) Dykstra, Matthew C.; Fowler, Wallace T.; Lightsey, E. GlennPresently, there are two main methods of launching a cube satellite into Earth orbit. The first method is to purchase a secondary payload slot on a major launch vehicle. For the second method, the satellite must first be transported via a major launch vehicle to the International Space Station. From there, the satellite is loaded into one of two deployment mechanisms, and deployed at a specified time. In each case, the satellite's initial orbit is not accurately known. For ground operators this poses a problem of position uncertainty. In order to solve this problem, a satellite tracking algorithm was developed to use an initial two-line element set for coarse orbit prediction, followed by Doppler measurements for continuous processing and updating. The system was tested using simulated data. The analysis showed that this low-cost, scalable system will satisfy the tracking requirements of many cube satellite missions, including current missions at the University of Texas.Item Three essays in econometrics(2011-05) Shen, Shu; Donald, Stephen G.My dissertation includes three essays that examine or relax classical restrictive assumptions used in econometrics estimation methods. The first chapter proposes methods for examining how a response variable is influenced by a covariate. Rather than focusing on the conditional mean I consider a test of whether a covariate has an effect on the entire conditional distribution of the response variable given the covariate and other conditioning variables. This type of analysis is useful in situations where the econometrician or policy maker is interested in knowing whether a variable or policy would improve the distribution of the response outcomes in a stochastic dominance sense. The response variable is assumed to be continuous, while both discrete and continuous covariate cases are considered. I derive the asymptotic distribution of the test statistics and show that they have simple known asymptotic distributions under the null by using and extending conditional empirical process results given by Horvath and Yandell (1988). Monte Carlo experiments are conducted, and the tests are shown to have good small sample behavior. The tests are applied to a study on father's labor supply. The second chapter is based on previous joint work with Jason Abrevaya. It considers estimation of censored panel-data models with individual-specific slope heterogeneity. The slope heterogeneity may be random (random-slopes model) or related to covariates (correlated-random-slopes model). Maximum likelihood and censored least-absolute deviations estimators are proposed for both models. Specification tests are provided to test the slope-heterogeneity models against nested alternatives. The proposed estimators and tests are used for an empirical study of Dutch household portfolio choice. Strong evidence of correlated random slopes for the age variables is found, indicating that the age profile of portfolio adjustment varies significantly with other household characteristics. The third chapter proposes specification tests in models with endogenous covariates. In empirical studies, econometricians often have little information on the functional form of the structural model, regardless of whether covariates in model are exogenous or endogenous. In this chapter, I propose tests for restricted structural model specifications with endogenous covariates against the fully nonparametric alternative. The restricted model specifications include the nonparametric specification with a restricted set of covariates, the semiparametric single index specification and the parametric linear specification. Test statistics are “leave-one-out” type kernel U-statistic as used in Fan and Lee (1996). They are constructed using the idea of the control function approach. Monte Carlo results are provided and tests are shown to have reasonable small sample behavior.