State Estimation of Integrated Navigation System Based on Neural Network

To estimate the state of integrated navigation system in serious interferential surroundings, the conventional filtering algorithms cant satisfy precision requirements. The paper introduces Elman network to resolve this problem and explains its designing means for estimating states. Its training algorithm is analyzed in detail and the approach to obtain swatch is also provided. Simulations are made by optimized algorithm and original algorithm. In the end, both the conventional filtering algorithm and the trained Elman network are used to estimate state of INS/GPS integrated navigation system. Simulation results show that the method is valid and practical.