Application of RBF Neural Network in Transfer Alignment of INS

被引：0

作者：

Wang Xibin ^{[1
]}

Zhao Guorong ^{[1
]}

机构：

[1] Naval Aeronaut & Astronaut Univ, Dept Control Engn, Yantai 264001, Peoples R China

来源：

PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION AND INSTRUMENTATION, VOL 4 | 2008年

关键词：

RBF neural network; carrier aircraft; INS; transfer alignment; Kalman filter;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Considering the character of Kalman filter's bad real-time qulity when system step is high, RBF neural network is applied to transfer alignment for carrier aircraft's INS. Through training of the sample of the input and output of Kalman filter, the output of neural network could be got, and realize the function of estimation of transfer alignment of INS were realized. Simulation results show that with the application of RBF neural network in transfer alignment can not only get the precision similar to Kalman filter, but also reduce the calculating time of system efficiently and raise the real-time quality.

引用

页码：1868 / 1871

页数：4

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