TY - GEN
T1 - Roll estimation algorithm based on Sage-Husa adaptive Kalman filtering with rotation criteria
AU - Jiawei, Wang
AU - Keyu, Qi
AU - Guotai, Xu
AU - Rongzhao, Qian
AU - Jie, Yan
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - According to the problem of increasing error caused by irresistible measuring noise in traditional EKF method within trajectory, a new solution of roll estimation for correction fuze, enlightened by axial output of gyro can be treated as rotation compensation for system noise, using SHAKF with rotation criteria is proposed. Firstly, based on the simulating comparison of estimation precision between traditional EKF and SHAKF methods, the result indicates that the roll measuring error of the new solution conspicuously lower than that of EKF's, the mean value of measuring error is 0.26deg and the variance of that is 0.97deg, that means the adaptivity offilter can follow the innovation to make estimated state convergence and eventually decreases the absolute error of roll angle. Furthermore, the new SHAKF algorithm is also verified by in-lab testing with MEMS three-Axis turntable under an actually varying rotation setting, and the result shows that the estimation error always below 4.2degs in dynamic range changing from 30r/s to 1r/s.
AB - According to the problem of increasing error caused by irresistible measuring noise in traditional EKF method within trajectory, a new solution of roll estimation for correction fuze, enlightened by axial output of gyro can be treated as rotation compensation for system noise, using SHAKF with rotation criteria is proposed. Firstly, based on the simulating comparison of estimation precision between traditional EKF and SHAKF methods, the result indicates that the roll measuring error of the new solution conspicuously lower than that of EKF's, the mean value of measuring error is 0.26deg and the variance of that is 0.97deg, that means the adaptivity offilter can follow the innovation to make estimated state convergence and eventually decreases the absolute error of roll angle. Furthermore, the new SHAKF algorithm is also verified by in-lab testing with MEMS three-Axis turntable under an actually varying rotation setting, and the result shows that the estimation error always below 4.2degs in dynamic range changing from 30r/s to 1r/s.
KW - 2-D Course Correction Fuze
KW - dual-spin stabilized projectile
KW - roll estimation
KW - rotation compensation
KW - Sage-Husa adaptive Kalman filtering
UR - https://www.scopus.com/pages/publications/85047193028
U2 - 10.1109/ICEMI.2017.8265931
DO - 10.1109/ICEMI.2017.8265931
M3 - 会议稿件
AN - SCOPUS:85047193028
T3 - ICEMI 2017 - Proceedings of IEEE 13th International Conference on Electronic Measurement and Instruments
SP - 155
EP - 161
BT - ICEMI 2017 - Proceedings of IEEE 13th International Conference on Electronic Measurement and Instruments
A2 - Juan, Wu
A2 - Jiali, Yin
A2 - Qi, Zhang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2017
Y2 - 20 October 2017 through 22 October 2017
ER -