Online SINS/GPS Integrated Navigation for AUV with RBFNeural Network
The strapdown inertial navigation system is usually employed to determine the attitude, velocity and position of an Autonomous Underwater Vehicle (AUV) for its specific advantage of small volume. The navigation accuracy provided by the SINS, which employs accelerometers and gyroscopes, deteriorates with time. Consequently, an external aiding source such as Global Positioning System (GPS) can be employed to reduce the error growth in the SINS. The GPS aided SINS system provides enhanced positioning accuracy of the AUV compared to that of a standalone SINS technique. A new method based on wavelet package multi-resolution analysis and RBF neural network to fuse the GPS and the SINS data for an AUV application was presented in this paper. It was proved from the experiments that navigation accuracy was improved substantially between GPS position fixes with the proposed method.
Autonomous Underwater Vehicle Strapdown Inertial Navigation System Global Positioning System Radial Basis Function neural network Wavelet Package Multi-resolution Analysis
WANG Qi XU Xiao su
School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China
国际会议
北京
英文
2007-08-05（万方平台首次上网日期，不代表论文的发表时间）