TY - GEN
T1 - An improved Federated Filter navigation algorithm for UAV
AU - Liu, Xuhang
AU - Liu, Xiaoxiong
AU - Yang, Yue
AU - Zhang, Weiguo
AU - Gao, Yanzhao
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - In the UAV (Unmanned Aerial Vehicle) integrated navigation system, considering the poor fault tolerance, inaccurate system model and robustness of the classic GPS/INS (Inertial Navigation System) integrated navigation algorithm, an improved Federated Filter navigation algorithm is put forward in this paper. Firstly, the GPS/INS/MAG (magnetometer) Federated Filter algorithm based on the theory of federated filter was designed. Secondly, the Adaptive Fading Kalman Filter algorithm and Robust Kalman Filter algorithm are introduced into the two sub-filters of the federated filter algorithm to suppress the interference of inaccurate system model and sensor errors on the filter results. The simulation results show that the Federated Filter model is effective and the improved Federated Filter algorithm can effectively enhance the attitude angle accuracy and suppress the influence of sensor error on the filter result.
AB - In the UAV (Unmanned Aerial Vehicle) integrated navigation system, considering the poor fault tolerance, inaccurate system model and robustness of the classic GPS/INS (Inertial Navigation System) integrated navigation algorithm, an improved Federated Filter navigation algorithm is put forward in this paper. Firstly, the GPS/INS/MAG (magnetometer) Federated Filter algorithm based on the theory of federated filter was designed. Secondly, the Adaptive Fading Kalman Filter algorithm and Robust Kalman Filter algorithm are introduced into the two sub-filters of the federated filter algorithm to suppress the interference of inaccurate system model and sensor errors on the filter results. The simulation results show that the Federated Filter model is effective and the improved Federated Filter algorithm can effectively enhance the attitude angle accuracy and suppress the influence of sensor error on the filter result.
KW - Adaptive Fading Kalman Filter
KW - Federated Filter
KW - Robust Kalman Filter
KW - UAV
UR - https://www.scopus.com/pages/publications/85080058077
U2 - 10.1109/CAC48633.2019.8996773
DO - 10.1109/CAC48633.2019.8996773
M3 - 会议稿件
AN - SCOPUS:85080058077
T3 - Proceedings - 2019 Chinese Automation Congress, CAC 2019
SP - 1621
EP - 1625
BT - Proceedings - 2019 Chinese Automation Congress, CAC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Chinese Automation Congress, CAC 2019
Y2 - 22 November 2019 through 24 November 2019
ER -