北京理工大学学报(英文版)
北京理工大學學報(英文版)
북경리공대학학보(영문판)
JOURNAL BEIJING INSTITUTE OF TECHNOLOGY
2003年
3期
230-235
,共6页
Hopfield neural network%dead reckoning%filtering and estimation%vehicle navigation
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.
