Identification of hydrodynamic coefficients of AUV in the presence of measurement biases

Date
2021-11-23
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Source Title
Institution of Mechanical Engineers. Proceedings. Part M: Journal of Engineering for the Maritime Environment
Print ISSN
1475-0902
Electronic ISSN
2041-3084
Publisher
Sage Publications
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Language
English
Type
Article
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Abstract

This paper mainly presents the parameter identification method developed from a Least Square Estimation (LSE) algorithm to estimate hydrodynamic coefficients of Autonomous Underwater Vehicle (AUV) in the presence of measurement biases. LSE based parameter determination method is developed to obtain unbiased estimated values of hydrodynamic coefficients of AUV from biased Inertial Navigation System (INS) measurements. The proposed parameter identification method consists of two phases: in the first phase, high precision INS and its auxiliary instrument including compass, pressure depth sensor, and Doppler Velocity Log (DVL) are designed as Integrated Navigational System coupled with Complementary Kalman Filter (CKF) to determine hydrodynamic coefficients of AUV by removing the INS measurement biases; in the second phase, LSE based parameter identification method is applied to the model in the first phase for obtaining unbiased estimated values of hydrodynamic coefficients of AUV. In this paper, a method for identifying the yaw and sway motion dynamic parameters of an AUV is given. Various maneuvering scenarios are verified to assess the parameter identification method employed. The simulation results indicate that using the CKF based Integrated Navigation System together with unbiased measurement conversion could produce better results for estimating the hydrodynamic coefficients of AUV.

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Keywords
Parameter identification, Least square estimation, Measurement bias, Kalman filter, Modeling of autonomous underwater vehicle, Integrated navigational system
Citation
Published Version (Please cite this version)
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