H_∞ Filter Technology in Integrated Navigation System of AUV

To improve the autonomous underwater vehicle (AUV) navigation accuracy, strap-down inertial navigation system (SINS) , Doppler velocity sonar (DVS) and terrain aided navigation (TAN) were adopted in the AUV integrated navigation system. Mathematical models of the AUV integrated navigation system and an observation model of the chosen navigation sensors were built according to the system simulation data. An improved filter based on radial basis function (RBF) neural network for adjusting the information sharing factors was designed and implemented in the AUV integrated navigation system. Simulation results show that the navigation accuracy is improved obviously with the specified sensors andH_∞filter in the case of colored noise. The novel integrated navigation system can effectively suppress the divergence of the filter, improve the fault tolerance ability, and greatly raise the navigation accuracy.