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2019 | OriginalPaper | Buchkapitel

5. Error Data Detection

verfasst von : Dewang Chen, Ruijun Cheng

Erschienen in: Intelligent Processing Algorithms and Applications for GPS Positioning Data of Qinghai-Tibet Railway

Verlag: Springer Berlin Heidelberg

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Abstract

There are a large number of measurement data points of GPS that are distributed on Qinghai–Tibet railway with a length of 1142 km. Due to various measurement reasons, there are inevitably some measurement errors. It is very important to develop a method to detect possible errors from all data points, and thus the reliability of GPS data can be improved by modifying or re-measuring them. Four error modes based on expert knowledge exist in the measurement data, including redundant measurement, sparse measurement, back-and-forth measurement, and large angle change. For the four error modes of the measurement data, four algorithms need to be developed to detect the possible errors of the corresponding data points. In order to remove repeated error data points and effectively display possible errors with different algorithms, an integrated error detection method is proposed by reasonably assembling four algorithms.

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Metadaten
Titel
Error Data Detection
verfasst von
Dewang Chen
Ruijun Cheng
Copyright-Jahr
2019
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-662-58970-0_5

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