| Filtering and Estimation of Vehicular Dead Reckoning System Based on Hopfield Neural Network |
| |
| 引用本文： | 毕军,付梦印,张启鸿. Filtering and Estimation of Vehicular Dead Reckoning System Based on Hopfield Neural Network[J]. 北京理工大学学报(英文版), 2003, 12(3): 230-235 |
| |
| 作者姓名： | 毕军 付梦印 张启鸿 |
| |
| 作者单位： | DepartmentofAutomaticControl,SchoolofInformationScienceandTechnology,BeijingInstituteofTechnology,Beijing100081,China |
| |
| 摘 要： | The algorithm of Hopfield neural network filtering and estimation is studied. The model of vehicular dead reckoning system fitting for the algorithm is constructed, and the design scheme of system filtering and esti-mation based on Hopfield network is proposed. Compared with Kalman filter, the algorithm does not require very precise system model and the prior knowledge of noise statistics and does not diverge easily. The simulation results show that the vehicular dead reckoning system based on Hopfield network filtering and estimation has the good position precision, and needn‘t require the inertial sensors with high precision. Therefore, the algorithm has the good practicability.
|
| 关 键 词： | 航位推测系统 GPS 全球定位系统 神经网络 过滤 船舶 导航系统 估算 |
| 收稿时间： | 2002-07-02 |
Filtering and Estimation of Vehicular Dead Reckoning System Based on Hopfield Neural Network |
| |
| BI Jun,FU Meng yin and ZHANG Qi hong. Filtering and Estimation of Vehicular Dead Reckoning System Based on Hopfield Neural Network[J]. Journal of Beijing Institute of Technology, 2003, 12(3): 230-235 |
| |
| Authors: | BI Jun FU Meng yin ZHANG Qi hong |
| |
| Affiliation: | Department of Automatic Control, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China;Department of Automatic Control, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China;Department of Automatic Control, School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China |
| |
| Abstract: | The algorithm of Hopfield neural network filtering and estimation is studied. The model of vehicular dead reckoning system fitting for the algorithm is constructed, and the design scheme of system filtering and estimation based on Hopfield network is proposed. Compared with Kalman filter, the algorithm does not require very precise system model and the prior knowledge of noise statistics and does not diverge easily. The simulation results show that the vehicular dead reckoning system based on Hopfield network filtering and estimation has the good position precision, and needn't require the inertial sensors with high precision. Therefore, the algorithm has the good practicability. |
| |
| Keywords: | Hopfield neural network dead reckoning filtering and estimation vehicle navigation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《北京理工大学学报(英文版)》浏览原始摘要信息 |
|
点击此处可从《北京理工大学学报(英文版)》下载全文 |
