GPS time correlation and its implication for precise navigation

Abstract

The Global Positioning System (GPS) is a satellite navigation system which, when fully operational, "will provide highly accurate position and velocity information in three dimensions, as well as precise time, to users around the globe 24 hours a day" (Anon, 1990). GPS can be operated under all weather conditions, with the only restriction being that the user must be able to receive radio signals from the satellites. Such a comprehensive positioning system has never been previously available, and thus GPS is currently being used for a diverse range of applications. This thesis is focused at the application of GPS for the offshore oil industry which is requiring increasingly higher instantaneous positioning accuracies. The GPS system and real-time positioning techniques are described, along with the main error sources that limit the available accuracy. The suitability of using GPS observations in a standard set of mathematical algorithms, the Kalman filter, in order to obtain position and velocity information has been examined. This is carried out by analysing the observations in order to determine some statistical properties that are usually ignored during the processing and data spanning a two year period has been analysed. The effect that these properties have on the resultant position and its precision was ascertained, finding that position discrepancies were insignificant but their associated precisions were highly dependent on the statistical properties were highly dependent of the data sets. Along similar lines., the ability of the Kalman filter to detect blunders, or gross errors, within GPS-type observations was analysed showing that the relevant test statistics performed sub-optimally and, again, this was dependent on the properties of the data.