TY - JOUR
T1 - An improved inertial matching algorithm for hull deformation with large misalignment angle
AU - Xu, Dongsheng
AU - Peng, Xiafu
AU - Zhang, Xiaoli
AU - Yang, Gongliu
AU - Hu, Xiaoqiang
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - Inertial matching measurement method has been widely used to measure hull deformation in real time to establish a unified attitude reference for ships in previous decades, but most current methods were based on linear error model which adopted small angle approximation. Therefore, the large misalignment angle in the hull deformation will bring great challenges to the accuracy of inertial matching measurement methods. In order to solve this problem, we divided the hull deformation with large misalignment angle into two parts: large angle based on coarse registration and small angle of the residual part. Three improvements were made as the following: (1) The quaternion optimization method (Q) was utilized to get the coarse registration result; (2) Based on the result, we derived a brand-new residual small-angle measurement algorithm. (3) We introduced neural network Karman filter (NNKF) to calculate the hull deformation in real time to further reduce the nonlinear error of the system. The experiment results illustrated that the proposed method, namely, Q-NNKF, can accurately measure the hull deformation in real time and effectively suppressed the nonlinear error caused by large misalignment angle.
AB - Inertial matching measurement method has been widely used to measure hull deformation in real time to establish a unified attitude reference for ships in previous decades, but most current methods were based on linear error model which adopted small angle approximation. Therefore, the large misalignment angle in the hull deformation will bring great challenges to the accuracy of inertial matching measurement methods. In order to solve this problem, we divided the hull deformation with large misalignment angle into two parts: large angle based on coarse registration and small angle of the residual part. Three improvements were made as the following: (1) The quaternion optimization method (Q) was utilized to get the coarse registration result; (2) Based on the result, we derived a brand-new residual small-angle measurement algorithm. (3) We introduced neural network Karman filter (NNKF) to calculate the hull deformation in real time to further reduce the nonlinear error of the system. The experiment results illustrated that the proposed method, namely, Q-NNKF, can accurately measure the hull deformation in real time and effectively suppressed the nonlinear error caused by large misalignment angle.
KW - Inertial matching measurement
KW - hull deformation algorithm
KW - large misalignment angle
KW - neural network Kalman filter
UR - https://www.scopus.com/pages/publications/85101748663
U2 - 10.1109/ACCESS.2021.3061263
DO - 10.1109/ACCESS.2021.3061263
M3 - 文章
AN - SCOPUS:85101748663
SN - 2169-3536
VL - 9
SP - 36634
EP - 36644
JO - IEEE Access
JF - IEEE Access
M1 - 9360610
ER -