Fuzzy Adaptive Filtering Algorithm Used in Autonomous Underwater Vehicle Integrated Navigation System

Fuzzy Adaptive Filtering Algorithm Used in Autonomous Underwater Vehicle Integrated Navigation System

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In complex underwater environments, the measurement noise model honeywell df300 n95 of autonomous underwater vehicle(AUV) navigation system will change with many uncertainties.Besides, the statistical characteristics of noise are difficult to be obtained accurately.For more precise state estimates, this paper introduces an adaptive filter based on fuzzy logic, which makes the measurement noise covariance matrix adaptively adjust to the accurate one.

In order to verify its validity, the proposed algorithm is used in a SINS/MCP/DVL/TAN integrated navigation system.The simulation results show that when dealing with the unstable measurement noise, the proposed filter has the higher degree of accuracy compared with the Sage-Husa adaptive filter.The east and north velocity errors of the proposed filter are reduced by 27.

0% and 42.0% respectively.The latitude and longitude errors are madelaine chocolate hearts reduced by 49.

4% and 58.0% respectively.