The Application of Recurrent Neural Networks in the GPS Vehicle Navigation Positioning Prediction
This paper applies recurrent neural networks in the GPS vehicle navigation positioning prediction. A technique of predicting the vehicle positioning information based on the recurrent neural networks with the GPS receiver losing the GPS positioning signals is presented in this paper. The dynamic backpropagation algorithm is used to train the diagonal recurrent neural networks in the pattern of tracking study to predict the future vehicle positions in a limited period. Numerical training and studying examples show that the diagonal recurrent neural networks can give relatively accurate and successive predictions about the future vehicle positions when the receiver loses the GPS signals in a limited period.
Recurrent Neural Network GPS Vehicle Navigation Positioning Prediction
Deng Minghui Wei Jinchen Xu Dingjie
Automation College, Harbin Engineering University
国际会议
北京
英文
133-137
2007-11-04（万方平台首次上网日期，不代表论文的发表时间）