INS, GPS, and Photogrammetry Integration for Vector Gravimetry Estimation

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)