Hydrodynamic Parameter Identification Techniques for UUV Models: A Systematic Literature Review

Raguvaran S., R. Pavithra

Abstract


The utility of any mathematical model for UUV flight is fundamentally constrained by the accuracy of its underlying physical parameters, such as added mass, damping coefficients, and thruster constants. This systematic literature review (SLR) offers an exhaustive evaluation of methodologies used to identify these parameters, synthesizing research from over 180 peer-reviewed publications. We categorize the state-of-the-art into three primary methodological streams: static experimental characterization, offline batch estimation, and online recursive identification. Static methods, including wind tunnels and pendulum-based inertia measurement, are analyzed for their precision versus high cost. Offline batch methods, such as Least Squares and Maximum Likelihood Estimation, are reviewed for their ability to process large datasets to extract global parameter sets. The review places special emphasis on online recursive identification, where techniques like Extended Kalman Filters (EKF) and Model Reference Adaptive Systems (MRAS) update parameter estimates in real-time. This is critical for UUVs experiencing significant state changes, such as those carrying liquid payloads or undergoing structural damage. By providing a comprehensive taxonomy and comparative performance analysis, this SLR serves as a definitive guide for researchers tasked with the calibration of high-fidelity UUV simulators.

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