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Research of Adaptive Kalman Filter Algorithm Based on the Fuzzy Neural Network

Author: YuePeng
Tutor: ZhaoLin
School: Harbin Engineering University
Course: Navigation,Guidance and Control
Keywords: Inertial Navigation System (SINS) Global Positioning System (GPS) BP neural network Fuzzy controller Adaptive Kalman Filter
CLC: TP183
Type: Master's thesis
Year: 2007
Downloads: 308
Quote: 1
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Abstract


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.

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Artificial Neural Networks and Computing
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