M.Ing. / Vehicle attitude is the most significant of the navigational parameters in terms of its influence on accumulated dead reckoning errors. To determine the attitude of the host vehicle body, with respect to the earth, it is necessary to keep track of the orientation of the body axes with respect to the local earth navigational frame (north, east and down). The aim of this research is to investigate the feasibility and the enhancement of low cost inertial sensors (such as gyroscopes) by the addition of magnetometer and pitch and roll angle sensors. The focus of this research is on the use of low cost inertial measurement systems to determine the attitude of a vehicle body. Strapdown system principles and the estimation theory are applied to achieve this goal. Both Euler angles and Quatemions as attitude representation are implemented and compared with one another. Work is concentrated around the mathematical models for low cost sensors and the attitude system dynamics. A sensor cluster is constructed using three gyroscopes, a magnetometer and two inclinometers. These inertial sensors were integrated using a Kalman filter. The mathematics, calculations and principles used are universal for all attitude systems. Practical data was recorded after which it was filtered to illustrate the working of the Kalman filter. The addition of a magnetometer and two inclinometers are indeed feasible for enhancing the attitude obtained from the inertial sensors. The benefit associated with the gyroscopes, when the magnetometer readings are disturbed by external magnetic anomalies, where small and of little significance. This thesis fully describes the theory and approach followed to implement the Kalman filter, making this a good example of a Kalman filter implementation, especially with the MATLAB software realisation presented in the appendix.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:1861 |
| Date | 07 December 2011 |
| Creators | Goosen, Gerhardus Rossouw |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
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