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Research on the Carrier Phase Difference Dynamic Positioning

Author: WangCheng
Tutor: YangJianHua
School: Chang'an University
Course: Geodesy and Survey Engineering
Keywords: carrier phase relative positioning slip detection LAMBDA robust estimation Kalman filtering
CLC: P228.4
Type: Master's thesis
Year: 2010
Downloads: 247
Quote: 1
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Abstract


Due to the trend of GPS development, dynamic positioning will has vaster application prospect than static positioning in the future. While the technology of carrier phase difference can meet the high-precision of real time dynamic positioning. Therefore it’s significative to pitch into researching of dynamic positioning, and to solve the key problems of it. This can expand the application of GNSS.This thesis introduces the rationale of carrier phase relative positioning and its functional model. Some kinds of carrier phase difference observation equations are inferred. Also stochastic model of relative positioning, the position errors, and modification methods of that are elaborated. Then it brings regular expression in processing of measurement data. So there is another way to extract information of GPS by regular expression. Some basic problems are discussed in article, such as the calculation of satellites coordinates, GOP of satellite constellation and the selection of reference satellite. Therewith, it indicates some disadvantages of cycle slip detections in existence. A new slip detection method is proposed. There are several ways analyzed on it, for instance, statistical hypothesis, linear fitting, AR model, entropy estimating and analysis of variance. And the method of analysis of variance is appropriate for slip detection, since its demonstration is strict. Afterwards, a method called LAMBDA for integer ambiguity estimation is described. Then it elaborates.on the theory of kalman filtering. Moreover, robust estimation based on double factor parity model and equivalence variance-covariance applying for carrier phase relative positioning is in detail. Through example, it comes to a conclusion that both of the correlated robust kalman filtering have some predominance in data treating.

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CLC: > Astronomy,Earth Sciences > Surveying and Mapping > Geodesy > Satellite geodesy and space geodesy > Global Positioning System (GPS)
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