With the rapid development of multi-sensor data fusion technology, the integrated navigation system is becoming more and more complex, so the faulty of a single component will affect the whole navigation system. To improve the fault tolerance performance of integrated navigation system, a fault-tolerant integrated navigation algorithm combining Federal Kalman Filter (FKF) and Adaptive Kalman Filter (AKF) is proposed in this paper. Introducing adaptive factors into the structure of FKF can reduce the influence of sensor failures and modeling errors. The real flight data from multirotor unmanned aerial vehicles (UAVs) is used for simulation. And the result of simulation shows that the proposed federal adaptive fault-tolerant integrated navigation algorithm based on FKF and AKF can increase the filtering accuracy and reliability significantly.


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    Title :

    A Fault-Tolerant Navigation Method for Multirotor UAVs Based on Federal Adaptive Kalman Filter


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Yu, Xiang (editor) / Liu, Xiaoxiong (author) / Ju, Yu Ting (author) / Gao, Yan Zhao (author) / Li, Chang Ze (author)


    Publication date :

    2021-10-30


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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