1
Department of Electrical Engineering, Salman University of Kazerun, Fars , Iran.
2
Department of Electrical Engineering, Islamic Azad University, Kazerun Branch, Fars, Iran.
10.61186/masm.2025.2068625.1166
Abstract
The challenge of designing and implementing optimal data fusion methods that are both robust to uncertainties and simple enough for practical deployment has become a significant topic of interest in a wide range of navigation and positioning systems. In this study, inspired by the principles of Proportional-Integral-Derivative (PID) control theory and integrating them with the conventional structure of the standard Kalman filter, we propose a novel data fusion approach. This method is specifically designed to improve robustness against measurement uncertainties from the Doppler Velocity Log (DVL) sensor in an integrated marine navigation system based on INS/DVL. The proposed approach aims to enhance the system’s resilience without introducing excessive computational complexity. Simulation results demonstrate that the integrated navigation system using the proposed algorithm outperforms traditional Kalman filter-based systems in terms of accuracy and response time, particularly under conditions involving sensor errors or uncertainty. These findings highlight the potential of the method for real-world applications in marine navigation scenarios.
Rahgoshay,M. A. and Ansari,M. (2025). Robust PI-based Data Fusion Approach for an INS/DVL Autonomous Underwater Positioning System. (e733192). Mechanic of Advanced and Smart Materials, (), e733192 doi: 10.61186/masm.2025.2068625.1166
MLA
Rahgoshay,M. A. , and Ansari,M. . "Robust PI-based Data Fusion Approach for an INS/DVL Autonomous Underwater Positioning System" .e733192 , Mechanic of Advanced and Smart Materials, , , 2025, e733192. doi: 10.61186/masm.2025.2068625.1166
HARVARD
Rahgoshay M. A., Ansari M. (2025). 'Robust PI-based Data Fusion Approach for an INS/DVL Autonomous Underwater Positioning System', Mechanic of Advanced and Smart Materials, (), e733192. doi: 10.61186/masm.2025.2068625.1166
CHICAGO
M. A. Rahgoshay and M. Ansari, "Robust PI-based Data Fusion Approach for an INS/DVL Autonomous Underwater Positioning System," Mechanic of Advanced and Smart Materials, (2025): e733192, doi: 10.61186/masm.2025.2068625.1166
VANCOUVER
Rahgoshay M. A., Ansari M. Robust PI-based Data Fusion Approach for an INS/DVL Autonomous Underwater Positioning System. MASM, 2025; (): e733192. doi: 10.61186/masm.2025.2068625.1166