http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
GPS position determination using a nonlinear predictive filter
This thesis develops an algorithm for GPS position determination. The algorithm is based on a nonlinear predictive filter and is a non-iterative method which converges over time. This algorithm is shown to provide an optimal correction at each time-step. The predictive filter is compared with nonlinear least squares using both ground-based and space-based simulations. Results show that the position estimates of the predictive filter are nearly identical to nonlinear least squares for all cases except those with very high velocities, such as an orbiting satellite. The computational workload of the predictive filter is shown to be significantly less than that of nonlinear least squares.
Issued also on microfiche from Lange Micrographics.
Includes bibliographical references (leaves 69-71).