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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.

An Improved Inertial Matching Algorithm for Hull Deformation With Large Misalignment Angle