Optimal Design of Network for Control of Total Station Instruments
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
This thesis uses the Minimum Norm Quadratic Unbiased Estimation (MINQUE) to estimatestandard deviation of observations of a total station. Different setups are created byaltering the number of stations and targets and their relative position in the network tostudy the effect that different setups have to the estimation and define what are importantto minimize the effect of the setup to the estimation.A lot of research has been done around methods for estimation of variance and covariancecomponents, since it is useful in many fields. Various approaches exists to solve theproblem of variance components estimation. Geodesy is a special case, were their often isa apriori knowledge of how well an instrument is able to record measurements. There isan ISO-standard for testing and verification of geodetic instrument but also an alternativeapproach the KTH-Total Station Check.For the estimation three main types of setups were defined and used in the simulation.These main types were then altered to see how different changes to the setup effect theoverall estimation. The alterations were changes in distance between station and targets,changes in vertical distance between stations and targets and the amount of observationscarried out by adding more stations and targets to the setups.The result of the simulations shows that the tested changes in the setups do effectthe estimation. It was not possible to determine by how much for each change, becausea change in vertical displacement also meant a change in angles and distance betweenthe station and the target. Increasing the amount of stations and targets or one of themshows that standard deviation of the estimation becomes smaller. The effect can be seenindependent of which type of setup that is used. The most important factor to how goodthe estimation will be is the amount of observations.
Place, publisher, year, edition, pages
2015. , 55 p.
TRITA-GIT EX, 15-004
Other Civil Engineering
IdentifiersURN: urn:nbn:se:kth:diva-172426OAI: oai:DiVA.org:kth-172426DiVA: diva2:848089
School of Architecture and the Built Environment (ABE) - Master of Science in Engineering