The attitude angle information of Unmanned Underwater Vehicle (UUV) is an important parameter information for UUV navigation control and navigation safety. This article proposes a combined filtering algorithm using Kalman filtering as the front filter and Mahony Kalman filtering as the back filter to improve the accuracy of attitude angle calculation for unmanned underwater vehicles. The front-end Kalman filter is used to update the optimal estimation of the inertial sensor, while the back-end Mahony Kalman filter updates the optimal estimation of the attitude angle. Based on the MPU6050 and HMC5883L inertial sensors, a nine axis UUV attitude detection system with STM32 as the main control is designed for attitude information data collection. The experimental results indicate that the combined filtering algorithm successfully reduces sensor noise, minimizes environmental interference, and enhances the accuracy of attitude calculations, thus exhibiting practical utility.


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    Title :

    Attitude Calculation of Unmanned Underwater Vehicle Based on Multi Sensor Data Fusion


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Deng, Yimin (editor) / Wang, Gao (author) / Wang, Yongjun (author) / Li, Zhi (author)

    Conference:

    International Conference on Guidance, Navigation and Control ; 2024 ; Changsha, China August 09, 2024 - August 11, 2024



    Publication date :

    2025-03-04


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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