Abstract
D.Ing.
Aerial Vehicle (UAV)-based observation system, by using the principles of strapdown inertial measurement
and navigation systems. Effort is concentrated around the mathematical implementation thereof and analysis
and proof of the concept in a computer simulation environment. Although the principles of the strapdown
system approach to camera-to-target vector estimation are universal to any type of airborne platform that can
carry the observation payload, the application thereof is specifically tailored for a UAV system. More
specifically, the operational scenario and UAV parameters of a typical close-range UAV system that is used
for artillery observation, is used in the derivation of the models and equations.
The secondary objective of this research is to derive a realizable mathematical implementation for this
strapdown system based camera-to-target vector estimation methodology, by performing a systematic tradeoff
between the use of Euler angles and quaternions for describing the camera-to-target vector, and by
incorporating the principles of Kalman filtering.
This dissertation fully describes the approach that was followed in the derivation of the strapdown system
equations for the camera-to-target vector estimation. The mathematical models and principles used are
universal for any airborne targeting application with a real-time video down-link.
The results as presented in this dissertation, prove that the methodology provides satisfactory results in both
a pure digital computer simulation environment, as well as in a digital computer simulation that is hybridized
with experimentally determined sensor outputs. It has led to a realizable and workable implementation that
could form the basis of practical implementation thereof in operational targeting systems. It further proves
that the slant range between a camera and a stationary target on the ground, can be estimated effectively
without the use of a laser rangefinder.