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Ohio State University. Division of Geodetic Science
Abstract
Presented in Partial Fulfillment of the Requirement for
the Degree Doctor of Philosophy in the Graduate
School of The Ohio State University.This work was supported by the U.S. Air Force under contract F19628-95-K- 0020 (Defense Mapping Agency funding) and by the National Imagery and Mapping Agency (formerly DMA) under contract NMA202-98-1-1110.Vector gravimetry using Inertial Navigation System (INS) in semi-kinematic
mode has been successfully applied. The integration of INS with other sensors, Global
Positioning System (GPS) or Gradiometer, for instance, has been under investigation for
many years. This dissertation examines the effect of photogrammetric derived orientation
on the INS sensor’s calibration and estimation of the gravity vector. The capability of
such integration in estimating the INS biases and drifts is studied. The underlying
principle, mathematical models, and error sources are presented and analyzed. The
estimation process utilizes the measurements of the Litton LN-100 inertial system,
Trimble 4000 SSI GPS dual frequency receiver, and metric frame camera. An optimal
filtering technique is used to integrate both GPS and INS on the level of raw
measurement for both systems. Introducing accurate and independent orientation
parameters, e.g., the photogrammetric source in this study, is demonstrated to enable
calibration of inertial gyros and bounding of their drift errors. This leads to improvement
in the horizontal components of the gravity vector estimation. The estimability and
improvement of the deflection of the vertical components are tested using flight test data
over Oakland, California, and a set of photogrammetric images simulated along the flight
trajectory.
The error statistics of the orientation measurement are modeled on the basis of the
variance-covariance matrix of a photogrammetric bundle adjustment of all photos. With
just a few ground control points at the beginning of the trajectory, the orientation
measurement errors along the trajectory are correlated significantly from epoch to epoch,
thus reducing the information content of the external orientation estimates.
The horizontal gravity component estimation is tested with respect to its
sensitivity to the variance of the orientation measurement errors, to its auto-correlation in
time, to the cross-correlation between angles, and to the amount of available ground
control. Although photogrammetric measurements, if uncorrelated, control orientation
errors as well as better than achievable with aircraft maneuvers, the inherent correlation
with a very limited amount of ground control provides only a small improvement. On the
basis of the simulation parameters, the gravity estimation error was reduced from 20
mgal (GPS/INS only) to about 9 mgal (best uncorrelated control) versus 17 mgal
(correlated control)
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