TY - GEN
T1 - A Novel Deformation Estimation Method Based on Robust Student's t Kalman Filter
AU - Zhang, Yonggang
AU - Xu, Geng
AU - Jia, Guangle
AU - He, Yongxu
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - In the severe maneuver of carriers, such as ship and aircraft, the large deformation may be induced, which will cause large errors in the transfer alignment of weapon system or the motion parameter estimation of synthetical earth observing system such as aerial mapping equipment and synthetic aperture radar. Conventional deformation model based on the second-order Gauss-Markov process with Gaussian noise will meet much restraint in practice environment. To solve the issue of non-Gaussian distributed process and measurement noises within the deformation model, this paper presented a novel Robust Student's t Kalman filter based deformation estimation method. By using the measurement information of inertial sensors, a high-precision deformation estimation is able to be achieved. The mathematical simulation results could reveal the accuracy of deformation estimation based on our proposed method comparing with conventional method.
AB - In the severe maneuver of carriers, such as ship and aircraft, the large deformation may be induced, which will cause large errors in the transfer alignment of weapon system or the motion parameter estimation of synthetical earth observing system such as aerial mapping equipment and synthetic aperture radar. Conventional deformation model based on the second-order Gauss-Markov process with Gaussian noise will meet much restraint in practice environment. To solve the issue of non-Gaussian distributed process and measurement noises within the deformation model, this paper presented a novel Robust Student's t Kalman filter based deformation estimation method. By using the measurement information of inertial sensors, a high-precision deformation estimation is able to be achieved. The mathematical simulation results could reveal the accuracy of deformation estimation based on our proposed method comparing with conventional method.
KW - Deformation estimation
KW - Kalman filter
KW - Student's t distribution
UR - https://www.scopus.com/pages/publications/85072376054
U2 - 10.1109/ICMA.2019.8816431
DO - 10.1109/ICMA.2019.8816431
M3 - 会议稿件
AN - SCOPUS:85072376054
T3 - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
SP - 695
EP - 700
BT - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Mechatronics and Automation, ICMA 2019
Y2 - 4 August 2019 through 7 August 2019
ER -