Establishment of a Pressure Variation Model for the State Estimation of an Underwater Vehicle

Abstract

This study presents a pressure variation model (PVM) derived from the regression analysis of dynamic pressure computed through numerical analysis to estimate the velocity of underwater vehicles. Furthermore, the drift angle estimation algorithm was developed using predicted velocities from PVM and pressure sensor differences. This approach estimates the single-motion states of underwater vehicles, such as straight, turning, and gliding. Furthermore, it confirms the viability of state estimation even in multiple motions involving turning and gliding motion with a drift angle and spiral motion. The comparison with numerical analysis results validated prediction accuracy within 15%.

Keywords

• artificial lateral line system (ALLSs)
• pressure variation model (PVM)
• pressure sensor array
• unmanned underwater vehicle (UUV)
• computational fluid dynamics (CFD)