Satellite-based navigation systems make it possible to determine the relative positions of points on the earth with centimetre or even millimetre level accuracy over baselines of up to several thousand kilometres. The highest possible accuracy can only be achieved if the carrier phase integer ambiguities can be resolved. In order to resolve the L1 and L2 integer ambiguities over long GPS baselines, the double difference residual ionospheric errors must be estimated for every satellite, every epoch. The resulting number of parameters is usually too large for estimation using ordinary least squares to be practical due to the time or computing resources needed for the processing. The technique currently used to efficiently estimate the parameters is known as pre-elimination. Pre-elimination divides the unknowns into parameters of interest (the coordinates and ambiguities) and nuisance parameters (the ionospheric path delays). The nuisance parameters are treated as stochastic variables and modelled as process noise, avoiding the need for them to be explicitly estimated. Whilst this approach is highly efficient, it makes assumptions about the stochastic behaviour of the residual ionospheric error that are not necessarily valid. The effectiveness of preelimination can be increased through the use of a deterministic model of the ionosphere. It is the hypothesis of this research that the ionospheric error can be more effectively estimated than is possible with pre-elimination, leading to more reliable ambiguity resolution for long baseline precise positioning. (For complete abstract open document)
| Identifer | oai:union.ndltd.org:ADTP/245512 |
| Creators | Brown, Neil E |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
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