Amirkabir University of Technology AUT Journal of Modeling and Simulation 2588-2953 54 2 2022 12 01 Tilt estimation using pressure sensors for unmanned underwater vehicle navigation 161 172 5014 10.22060/miscj.2022.21580.5290 EN Mostafa Amuei Faculty of Electrical and Computer Engineering, Malek-Ashtar University of technology, Tehran, Iran 0000-0003-1436-2603 Seyyed Mohammad Mehdi Dehghan Faculty of Electrical and Computer Engineering, Malek-Ashtar University of technology, Tehran, Iran 0000-0002-3835-0212 Hossien Nourmohammadi Northern Research Center for Science and Technology, Malek-Ashtar University of technology, Fereydunkenar, Iran 0000-0003-4885-4964 Mohammad Ali AlirezaPouri Faculty of Electrical and Computer Engineering, Malek-Ashtar University of technology, Tehran, Iran 0000-0002-9470-4089 Journal Article 2022 07 10 Since the Unmanned Underwater Vehicles (UUVs) don’t receive the Global Navigation Satellite System (GNSS) signals under the water, other aided measurements are needed to provide the required accuracy in tilt estimation including roll and pitch angle estimation. Conventional approaches for pressure-based tilt estimation, only consider the relation between the static pressure and the tilt as the measurement model. However, the performance of this approach depends on the dynamic pressure which is caused by the sea waves. This paper improves the accuracy of pressure-based tilt estimation using the more accurate of the measurement model. Also, the proposed approach considers the coupling between the axes of UUV. Due to the cost of the approach and the hardware limitations of installation pressure sensors, the proposed approach is implemented using two pressure sensors. An Extended Kalman Filter (EKF) is used for simultaneous tilt and gyroscopes measurement errors estimation. A Monte-Carlo simulation is developed to evaluate the performance of the proposed approach in comparison with INS only and the conventional static pressure-based tilt estimation. The simulation results show that tilt estimation performance of conventional approach is better than the INS only performance and the performance of proposed approach is better than the both of them. https://miscj.aut.ac.ir/article_5014_4424d2deec2f9468fb61e2db07ecd6b6.pdf