LONG-TERM OPERATIONAL MODEL OF AUTONOMOUS UNDERWATER VEHICLES (AUV) FOR MARITIME DEFENSE AND SECURITY
DOI:
10.5281/zenodo.21505231Published:
2026-07-20Downloads
Abstract
This study aims to develop a long-term operational model for Autonomous Underwater Vehicles (AUVs) to enhance maritime defense and security. It focuses on optimizing AUV deployment strategies, improving endurance and navigation efficiency, and integrating advanced technologies to support autonomous maritime operations. The research employs a descriptive-analytical approach, utilizing literature reviews, technical simulations, and expert validation. It examines the integration of energy-efficient propulsion, AI-based navigation, and acoustic communication systems to enhance AUVs' long-term operational capabilities. The study reveals that the implementation of AI-driven navigation, high-capacity energy storage, and robust underwater communication significantly improves AUVs’ endurance and mission effectiveness. However, challenges such as high procurement costs, environmental constraints, and cybersecurity risks must be addressed to ensure sustainable operations. The findings highlight the importance of developing local AUV manufacturing capabilities and enhancing interoperability with existing maritime defense systems. This research contributes to the advancement of autonomous maritime defense by proposing a scalable and adaptive AUV operational model. It provides strategic recommendations for defense planners and policymakers to strengthen Indonesia’s maritime surveillance and security infrastructure.
Keywords:
Autonomous Underwater Vehicles Maritime Defense Autonomous Navigation Acoustic Communication Maritime Security.References
[1] J. R. Anderson, “Unmanned Maritime Operations: Challenges and Future Prospects,” Nav. Technol. Rev., vol. 27, no. 4, pp. 50–68, 2021.
[2] T. Roberts, “The Role of Underwater Drones in Modern Naval Warfare,” Int. J. Marit. Def., vol. 16, no. 2, pp. 87–104, 2017.
[3] R. Abdullah and B. Setiawan, “Teknologi Navigasi Otonom pada AUV,” J. Teknol. Marit., vol. 15, no. 2, pp. 45–62, 2023.
[4] H. Gunawan, “Indonesia’s Maritime Strategy and the Role of Unmanned Systems,” J. Southeast Asian Def. Policy, vol. 12, no. 4, pp. 144–160, 2022.
[5] A. Prasetyo, “Keamanan Data pada Sistem Maritim,” J. Teknol. Inf., vol. 8, no. 1, pp. 110–125, 2023.
[6] Y. Nakamura, “AUV Operations in Strategic Maritime Regions: Lessons from the Indo-Pacific,” J. Def. Res., vol. 25, no. 4, pp. 55–73, 2022.
[7] P. Sanchez, “Battery Technologies for Long-Term Autonomous Operations of AUVs,” J. Eng. Mar. Syst., vol. 30, no. 1, pp. 135–152, 2021.
[8] J. Harrison, “Energy Efficiency in Autonomous Underwater Vehicles: Innovations and Limitations,” Mar. Technol. J., vol. 26, no. 2, pp. 34–50, 2018.
[9] P. Davies, “Acoustic Communication and Its Impact on Long-Term AUV Deployment,” Oceanogr. Res., vol. 31, no. 3, pp. 201–220, 2022.
[10] D. Lee and J. Evans, “AI-Based Autonomous Navigation in Unmanned Marine Vehicles,” J. Nav. Sci., vol. 28, no. 3, pp. 115–132, 2020.
[11] R. Kumar, “Cybersecurity Challenges in Maritime Autonomous Systems,” Int. J. Def. Cybersecurity, vol. 18, no. 2, pp. 112–130, 2023.
[12] L. Zhang, “The Future of Autonomous Maritime Systems: Trends and Strategic Implications,” Int. J. Nav. Strateg., vol. 20, no. 3, pp. 90–110, 2021.
[13] S. Martin and G. Reynolds, “Unmanned Underwater Vehicles for Asymmetric Warfare: Case Studies and Future Trends,” Def. Secur. J., vol. 21, no. 1, pp. 77–95, 2019.
[14] H. Tanaka, “AI and Sensor Integration in Autonomous Underwater Vehicles,” J. Mar. Robot., vol. 27, no. 2, pp. 40–58, 2020.
[15] U. S. D. of Defense, Autonomous Systems in Modern Military Strategy. Washington, DC: U.S, 2019.
[16] T. Chen and K. Lee, “Artificial Intelligence in Maritime Surveillance: Enhancing AUV Capabilities,” J. Mar. Eng., vol. 22, no. 1, pp. 55–70, 2019.
[17] G. Vaisman and M. Klein, “Advances in AUV Sensor Technologies for Maritime Surveillance,” J. Ocean. Eng., vol. 23, no. 4, pp. 188–202, 2018.
[18] J. W. Creswell, “Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.),” SAGE Publ., 2014.
[19] L. Wahyuni, “Implementasi Sistem Komunikasi Akustik pada AUV,” J. Ilmu Kelaut., vol. 9, no. 2, pp. 95–100, 2022.
[20] A. Jenkins and L. Marshall, “Autonomous Underwater Vehicles: Design and Applications in Maritime Defense,” Ocean Eng., vol. 82, no. 4, pp. 123–145, 2020.
[21] L. Radu, M. Fodor, and P. Ivanov, “Challenges in AUV Navigation and Efficiency in Defense Missions,” Int. J. Mar. Technol., vol. 27, no. 2, pp. 77–89, 2021.
[22] R. Smith and W. Zhao, “Hydrodynamic Simulation and Energy Efficiency of Autonomous Underwater Vehicles,” J. Underw. Robot., vol. 34, no. 6, pp. 206–220, 2019.
[23] H. Lee, D. Yang, and S. Kim, “Optimization of AUV Structures for Deep-Sea Operations,” Mar. Technol. Soc. J., vol. 54, no. 8, pp. 56–68, 2020.
[24] J. Kim and Y. Park, “AUV Threat Detection and Communication Systems: Validation Methods and Results,” Def. Technol. Rev., vol. 39, no. 1, pp. 10–21, 2021.
[25] R. Garcia, M. Johnson, and R. Patel, “Real-World Scenarios for Autonomous Vehicle Validation in
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Copyright (c) 2026 Tomy Ronaldi, Nizirwan Anwar
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