The Application of Self-adaption Kalman Filtering Algorithm Based on the Current Statistic Model in the Tram’s GPS Positioning
Trams often mix with other vehicles on the ground, so their accurate positioning is important for train dispatching and transportation safety. The method of combining speed sensors and GPS is usually adopted by the streetcars system in positioning area. In order to simplify the system, save cost, ca...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Electric Drive for Locomotives
2020-03-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2020.02.121 |
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| Summary: | Trams often mix with other vehicles on the ground, so their accurate positioning is important for train dispatching and transportation safety. The method of combining speed sensors and GPS is usually adopted by the streetcars system in positioning area. In order to simplify the system, save cost, calculate difficulty and accuracy, Kalman filter method was used to correct the GPS positioning information. Meanwhile, the current statistic model of maneuvering acceleration was adopted to describe the tram state, which was closed to the real movement of the tram. Through Matlab simulation, the GPS positioning message collected in the test site dealt and estimated by the Kalman filtering based on the current model. The result shows that the positioning result can follow the real movement of the tram better. In other words, the Kalman filtering based on the current model can improve the precision of positioning and the result may closer to the real value. |
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| ISSN: | 1000-128X |