Issued also as a Sc.D. thesis in the Dept. of Electrical Engineering, 1968. / Bibliography: p.103-104.

ESD-TR-67-466. / Bibliography: p.85. / Contract AF 19(628)-5167.

Reprinted from IEEE transactions on information theory, vol. IT-13, no.3, July 1967. / Bibliography: p. 501.

Based on a thesis in Electrical Engineering, 1966. / Bibliography: p.109-110. / Contract no. DA36-039-AMC-03200(E).

No description available.

Includes bibliographies.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Some modern spacecraft missions require precise knowledge of the attitude, obtained from the ground processing of on-board attitude sensors. A traditional 6-state attitude determination filter, containing three attitude errors and three gyro bias errors, has been recognized for its robust performance when it is used with high quality measurement data from a star tracker for many past and present missions. However, as higher accuracies are required for attitude knowledge in the missions, systematic errors such as sensor misalignment and scale factor errors, which could often be neglected in previous missions, have become serious, and sometimes, the dominant error sources. The star tracker data have gaps and degradation caused by, for example, the Sun and Moon blocking in the filed of view and data time tag errors. Thus, attitude determination based on the gyro data without using the star tracker data is inevitably required for most missions for the period when the star tracker is unable to provide accurate data. However, any gyro-based attitude errors would eventually grow exponentially because of the uncorrected systematic errors of gyros and the uncorrected gyro random noises. An improved understanding of the gyro random noise characteristics and the estimation of the gyro scale factor errors and gyro misalignments are necessary for precise attitude determination for some present and future missions. The 6-state filters have been extended to 15-state filters to estimate the scale factor and misalignment errors of gyros especially during a high-slew maneuver and the performance of theses filters has been investigated. During a starless period, the inevitable drift of the EKF solutions, which are caused by the uncorrected gyro’s systematic errors and the gyro random noises, can be replaced with the batch solutions, which are less affected by the data gap in the star tracker. Power Spectral Density and the Allan Variance Method are used for analyzing the gyro random noises in both ICESat and simulated gyro data, which provide better information about the process noise covariance in the attitude filter. Both simulated and real data are used for analyzing and evaluating the performances of EKF and batch algorithms. / text

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Fluctuation phenomena are important to many physical systems, such as the fusion plasma. Noise theory is used to study the time and space correlations of stationary Markovian fluctuations that are statistically homogeneous and isotropic. The relaxation of the fluctuations is modeled by the diffusion equation. The spatial correlations are modeled by the exponential decay. Based on these models, the correlation function and the power spectral density of random fluctuations. We also find that the fluctuation-induced transport coefficients may be estimated by the correlation length and the correlation time. The theoretical results are compared with the observed plasma density fluctuations from tokamak and helimak experiments.