GPS/INS Integration for Improved Aircraft Attitude Estimates
Date of Award
12-1991
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
Abstract
This report documents research into the design, implementation, and analysis of a post-mission navigation error estimation algorithm for the Electronic Counter-Countermeasures/Advanced Radar Test Bed (ARTB). In order to quantify the effects of Electronic Countermeasures (ECM) on a given radar accurately, extremely accurate navigation information for ARTB and a given test target must be available for use as reference or truth data. Presently, the ARTB navigation subsystem provides adequate accuracy in position and velocity; however, its computation of attitude does not meet the level of accuracy required for airborne radar flight testing. An extended Kalman filter algorithm is implemented in a filter-driving-filter configuration to integrate the outputs of a Global Positioning System Receiver 3A and a SNU 84-1 Inertial Navigation System in order to estimate and compensate for inertial navigation system errors. The specific objective of integrating the two systems is to enhance the accuracy of ARTB's attitude indications. Outputs from the 12-state GPS Kalman filter simulation are used as measurements in the 23-state Integration Kalman Filter. Monte Carlo simulations are run for measurement update intervals of 5, 10, and 15 seconds, and for both benign (less than 2-g) and highly dynamic (up to 9-g) flight scenarios. Cross-correlation between GPS Kalman filter estimation errors and true INS system errors is also examined. Results indicate that this i8ntegration scheme provides an increase in accuracy for position and velocity of up to 98%, and an increase in accuracy for attitude of up to 88% over the unaided INS alone.
AFIT Designator
AFIT-GE-ENG-91D-04
DTIC Accession Number
ADA243947
Recommended Citation
Bagley, Daniel T., "GPS/INS Integration for Improved Aircraft Attitude Estimates" (1991). Theses and Dissertations. 7337.
https://scholar.afit.edu/etd/7337