Fusion Attitude Solving Algorithm of Four-Rotor UAV Based on Improved Extended Kalman Filter

被引:0
|
作者
Sheng, GuangRun [1 ]
Gao, GuoWei [1 ,2 ]
机构
[1] Beijing Informat Sci & Technol Univ, Beijing Key Lab Sensor, Beijing, Peoples R China
[2] Beijing Informat Sci & Technol Univ, Key Lab Modern Measurement & Control Technol, Minist Educ, Beijing, Peoples R China
关键词
Quadrotor; Extended Kalman Filter (EKF); attitude solution; Information fusion;
D O I
10.1109/cac48633.2019.8996893
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The stability problem of the four-rotor aircraft in flight control is popular in the research of Quadrotors, and the attitude angle is an important flight control parameter for the four-rotor aircraft, which plays a very important role in stable flight. The solution of the attitude angle is actually the fusion of multi-sensor acquisition attitude information. This paper proposes an improved EKF filtering algorithm based on attitude solution. The attitude angle obtained by the complementary filtering is used as the observation variable of the EKF filter equation, The angular velocity of the gyroscope is used as a state variable. Then act on the real-time pose update calculation, thereby outputting the attitude angle information. And based on STM32 MCU to build a four-rotor aircraft experimental platform for performance verification. The results show that the designed algorithm is faster and more acurrate than the convergence rate, which can meet the requirements of precision and real-time performance of the quadrotor.
引用
收藏
页码:3296 / 3299
页数:4
相关论文
共 50 条
  • [1] Attitude Solving Algorithm and FPGA Implementation of Four-Rotor UAV Based on Improved Mahony Complementary Filter
    Zhu, Yanping
    Liu, Jing
    Yu, Ran
    Mu, Zijian
    Huang, Lei
    Chen, Jinli
    Chen, Jianan
    [J]. SENSORS, 2022, 22 (17)
  • [2] Multi-Rotor UAV Attitude Calculation Based on Extended Kalman Filter
    Zheng, Yajun
    Dong, Lu
    Wang, Qingling
    [J]. PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 478 - 483
  • [3] An Improved Target Tracking Algorithm Based on Extended Kalman Filter for UAV
    Li, Yibing
    Jiu, Mingyang
    Sun, Qian
    Wang, Yansong
    [J]. PROCEEDINGS OF THE 2018 IEEE 7TH ASIA-PACIFIC CONFERENCE ON ANTENNAS AND PROPAGATION (APCAP), 2018, : 435 - 437
  • [4] Adaptive Extended Kalman Filter Based on SOA Algorithm for UAV Attitude Solution
    Zhou, Guoqing
    Wu, Tingsheng
    [J]. SPIE-CLP CONFERENCE ON ADVANCED PHOTONICS 2022, 2023, 12601
  • [5] An Improved Four-Rotor UAV Autonomous Navigation Multisensor Fusion Depth Learning
    Liu, Liwen
    Wu, Yuanming
    Fu, Gui
    Zhou, Chao
    [J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [6] Application of the attitude estimation of the four-rotor aircraft based on quaternion and complementary filter
    Xu Yuanxiang
    Li Yueqiang
    [J]. PROCEEDINGS OF THE FIFTH INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1 AND 2, 2014, : 428 - 432
  • [7] Attitude Estimation of the Multi-rotor UAV Based on Simplified Adaptive Kalman Filter Algorithm
    Zhang, Xin
    Bai, Yue
    Xu, Zhijun
    Wang, Rijun
    [J]. PROCEEDINGS OF THE 2015 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT INFORMATION PROCESSING, 2015, 336 : 219 - 227
  • [8] Research on Attitude Control System of Four-Rotor UAV Based on Two Ring Control
    Chen, Di
    Qian, Kun
    Liu, Cong
    Zhu, Yu
    [J]. PROCEEDINGS OF 2020 IEEE 5TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2020), 2020, : 249 - 253
  • [9] Attitude information fusion method based on extended kalman filter
    Lu, Yanjun
    Chen, Yudi
    Zhang, Xiaodong
    Zhang, Taining
    [J]. Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2020, 41 (09): : 281 - 288
  • [10] Attitude Estimation for UAV Using Extended Kalman Filter
    Jing, Xiaofei
    Cui, Jiarui
    He, Hongtai
    Zhang, Bo
    Ding, Dawei
    Yang, Yue
    [J]. 2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2017, : 3307 - 3312