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Route Optimization for Active Sonar in Underwater Surveillance.
Mehmet Gokhan Metin1, Mumtaz Karatas2, Serol Bulkan1
1Department of Industrial Engineering, Marmara University, Istanbul 34854, Türkiye.
Sensors (Basel, Switzerland)
|July 12, 2025
Summary
This study optimizes mobile multistatic sonar networks (MSNs) for underwater surveillance. An Ant Colony Optimization (ACO) heuristic efficiently finds optimal source routes to maximize area coverage, outperforming traditional methods.
Area of Science:
- Oceanography
- Acoustics
- Robotics
Background:
- Multistatic sonar networks (MSNs) offer advanced underwater surveillance by using spatially distributed sources and receivers, unlike traditional monostatic systems.
- Optimizing the path of mobile sonar sources is crucial for maximizing the effectiveness of MSNs in underwater environments.
Purpose of the Study:
- To determine the optimal route for a mobile multistatic active sonar source to maximize area coverage.
- To develop and evaluate computational methods for solving the mobile source routing problem in MSNs.
Main Methods:
- A Mixed Integer Linear Program (MILP) formulation was developed to find optimal single-source routes within a hexagonal grid.
- An Ant Colony Optimization (ACO) heuristic was proposed as an efficient method for solving large-scale MSN routing problems.
Main Results:
- The study presents a novel MILP formulation for optimal source routing in MSNs.
- The proposed ACO heuristic demonstrates efficiency in solving complex routing instances.
- Numerical experiments validate the performance of both MILP and ACO methods.
Conclusions:
- The developed MILP and ACO approaches provide effective solutions for optimizing mobile source routes in multistatic sonar networks.
- These methods enhance underwater surveillance capabilities by maximizing area coverage.
- The research contributes to the advancement of autonomous underwater systems and surveillance technologies.
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