A study on the self-difference GPS positioning by dynamic and fictitious datum station
GPS positioning has a lot of error elements. In order to remove them, this paper advances a new method of GPS positioning-self-difference GPS positioning by a dynamic and fictitious datum station. The distance that a vehicle runs can be divided into many small regions. Every region sets up a fictiti...
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Published in | Proceedings of the IEEE International Vehicle Electronics Conference (IVEC'99) (Cat. No.99EX257) pp. 16 - 18 vol.1 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
1999
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Subjects | |
Online Access | Get full text |
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Summary: | GPS positioning has a lot of error elements. In order to remove them, this paper advances a new method of GPS positioning-self-difference GPS positioning by a dynamic and fictitious datum station. The distance that a vehicle runs can be divided into many small regions. Every region sets up a fictitious datum station. The foundation of the fictitious datum station demands three values: forecasting value; real-time value; and value of the last datum station). They are in all sent to a neural network that consists of three layer neurons. The output of the neural network is the coordinates of the fictitious datum station. The training of the network uses a BP algorithm. The decision function chooses a nonlinear Sigmoid function. The experiment has proved that the method can significantly improve positioning precision, and that the system also has rapid tracking ability. |
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ISBN: | 9780780352964 0780352963 |
DOI: | 10.1109/IVEC.1999.830608 |