Research Of Adaptive Kalman Filter Algorithm Based On The Fuzzy Neural Network

The need of Inertial Navigation System/Global Positioning System (SINS/GPS) augmentation system stems from the shortcoming of each individual technology. The stand-alone INS has superior short-term error performance, but position errors of INS are unbounded. On the other hand, long-term accuracy of GPS is good, but short-term accuracy is poor. The motivation for SINS/GPS integration is to develop a navigation system that overcomes the shortcomings of each system.The primary objective of this research is to improve he in-flight alignment and positioning performance of an integrated INS/GPS during a rendezvous scenario where noise processes are not exactly known. In order to accomplish this, the mathematical model of INS/GPS integrated navigation system are designed based on the positioning principle and the error analysis.When the noise processes are not exactly known, divergence problems will occur. In this paper, a fuzzy adaptive system is used to adjust the exponential weighting of a weighted Kalman filtering and prevent it from divergence. The simulation results show the fuzzy adaptive algorithm is robust and has high accuracy.