Fuzzy adaptive algorithm based on modified current statistical model for vehicle positioning
The singer model and current statistical model were first analyzed and compared. A modified scheme based on the two kinds of models was proposed. Moreover, a modified current statistical model based-fuzzy adaptive extended Kalman filter (MCS-FAEKF)algorithm was proposed to choose maneuvering model a...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2013-07-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.07.021/ |
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| Summary: | The singer model and current statistical model were first analyzed and compared. A modified scheme based on the two kinds of models was proposed. Moreover, a modified current statistical model based-fuzzy adaptive extended Kalman filter (MCS-FAEKF)algorithm was proposed to choose maneuvering model and adjust system noise covariance dynamically. The simulated results show that the algorithm could get more accurate and reliable performance for vehicle positioning compared with the current statistical model based-extended Kalman filter (CS-EKF) and Singer-EKF algo-rithms. |
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| ISSN: | 1000-436X |