Thesis (MScEng)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: This thesis presents the development of a state estimation system for use in an Autonomous Airborne Refueling (AAR) operation through the simulated implementation of GPS, monocular and stereoscopic vision, inertial measurement sensors and boom parameter measurement in combination with the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). A set of functional criteria for the estimation system was developed through an analysis of the control system input requirements and associated constraints. The estimation system is further developed by integrating the sensor configurations into the estimation algorithm structures through the derivation of the applicable mathematical models. Final sensor configurations are set based on a sensitivity analysis in which the effect of parameters such as sensor noise, placement and quantity are related to the accuracy with which the states are estimated. Uncertainty in the process noise, which is typically approximated, is overcome by adding an adaptive element to the estimation algorithms in which the current process noise is estimated allowing compensation for unmodeled process noise uncertainty. Finally twelve practical sensor configurations are established utilising unique combinations of the five sensors. Each configuration is simulated using both estimation algorithms after which all results are evaluated with respect to one another as well as to the minimum state accuracy criteria. Conclusions are presented based on the evaluation of the results followed by recommendation for future development. / AFRIKAANSE OPSOMMINGS: Die ontwikkeling van ’n toestandafskattingstelsel, spesifiek toegepas op outonome brandstofhervulling, word voorgelê in hierdie tesis. Hierdie ontwikkeling behels die implementering van GPS, monukulêre- en stereo-visie sensors, inersiële sensor eenhede en verbindingsarmsensors wat gebruik word in ’n Uitgebruide Kalman Filter (Extended Kalman Filter) en Geurlose Kalman Filter (Unscented Kalman Filter). ’n Volledige ontleding van die beheerstelsel se toevoervereistes en geassosieerde beperkings is gebruik om ’n stel beoordelingsmaatstawwe vir die toestandafskatting-stelsel te bepaal. Die stelsel is verder ontwikkel deur verskillende sensorkonfigurasies met die afskattingsalgoritmes te kombineer deur die afleiding van toepaslike wiskundinge modelle. Hierdie konfigurasies is verfyn deur ’n sensitiwiteitsanalise, waar die verwantskap tussen die effekte van sensorruis, sensorligging, hoeveelheid sensors ondersoek is met betrekking tot afskattingsakkuraatheid. Onsekerheid in die stelsel se prosesruis is deur ’n aanpassings substelsel hanteer, wat kompensasie vir ongemodeleerde onsekerheid moontlik maak. Twaalf praktiese sensorkonfigurasies is opgestel vanuit unieke kombinasies van die vyf sensore behartig in die projek. Hierdie konfigurasies is deur beide afskattingsalgoritmes gebruik om sodoende die akkuraatheid van die konfigurasies asook die afskattingsalgoritmes te evalueer met betrekking tot mekaar en aan die hand van die beoordelingsmaatstawwe vir die beheerstelsel. Die tesis is afgesluit deur gevolgtrekkings asook aanbevelings vir toekomstige navorsing.