Research on multi-model adaptive hull deformation measurement algorithm

Wang, Yanyan; Zhang, Ya; Wang, Kai; Wang, Zhuo; Chang, Jia-Ruey; Xu, Dianguo

doi:10.1109/plans46316.2020.9109889

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…As described in [10], x is the state vector, A is the system state transition matrix, B is the system noise matrix, and w is the system noise vector.…”

Section: B Establishment Of Nonlinear Filtering Modelmentioning

confidence: 99%

“…It is also unrealistic to determine the main frequency through spectrum analysis during the actual ship measurement. Otherwise, the observation noise is often time-varying or even unknown, which will also adversely affect the measurement accuracy [10]. Aiming at these two problems, the improved variable parameter multiple model algorithm based on ACKF (VPMM-ACKF) is proposed.…”

Section: B Adaptive Variable Parameter Multiple Model Algorithmmentioning

confidence: 99%

“…At present, the main methods of measuring ship deformation include the large steel tube reference method, the Bragg fiber grating method, the photogrammetry method, the dual frequency polarization light method, the liquid pressure measurement method and so on [10]- [14]. However, these methods suffer from low accuracy of measurement, complicated calculation, uninstrumentation, large structures, and requiring optical visibility, so they are not suitable for complicated maritime navigation environments [15]- [19].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Deformation Measurement Algorithm Based on Adaptive Variable Parameter Multiple Model for Large Ships

Wang

Zhang

et al. 2021

IEEE Trans. Instrum. Meas.

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Accurate measurement of ship deformation angle is of great significance for building a unified space attitude reference and improving the combat performance of the entire ship. However, many problems existing in the actual sailing process restrict its measurement accuracy severely, such as the time delay between measurement equipment, the unknown characteristics of measurement noise and the unknown model parameters of the dynamic deformation. This paper proposes an adaptive variable parameter multiple model (AVPMM) algorithm that can simultaneously solve these problems. Firstly, a time delay compensation algorithm is derived to suppress the influence of time delay on measurement accuracy; then an adaptive Cubature Kalman filter (ACKF) is designed based on the idea of adaptive filtering to suppress the influence of unknown characteristics of measurement noise; and finally an AVPMM algorithm is designed by combining the above ideas to reduce the impact of unknown model parameters of dynamic deformation. The results of simulation and turntable experiment show that this algorithm has good measurement accuracy and the error is less than 0.15 ′ .

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“…As described in [10], x is the state vector, A is the system state transition matrix, B is the system noise matrix, and w is the system noise vector.…”

Section: B Establishment Of Nonlinear Filtering Modelmentioning

confidence: 99%

Section: B Adaptive Variable Parameter Multiple Model Algorithmmentioning

confidence: 99%