# Route Optimization for Active Sonar in Underwater Surveillance

## TL;DR

This paper presents methods to optimize the route of a mobile sonar source in underwater surveillance to maximize area coverage.

## Contribution

A novel MILP formulation and an ACO heuristic for route optimization in multistatic sonar networks are proposed.

## Key findings

- The MILP formulation effectively determines optimal routes in small to medium-sized problems.
- The ACO heuristic provides near-optimal solutions for large-scale problems efficiently.
- Numerical experiments show the ACO heuristic performs comparably to the exact MILP solution.

## Abstract

Multistatic sonar networks (MSNs) have emerged as a powerful approach for enhancing underwater surveillance capabilities. Different from monostatic sonar systems which use collocated sources and receivers, MSNs consist of spatially distributed and independent sources and receivers. In this work, we address the problem of determining the optimal route for a mobile multistatic active sonar source to maximize area coverage, assuming all receiver locations are known in advance. For this purpose, we first develop a Mixed Integer Linear Program (MILP) formulation that determines the route for a single source within a field discretized using a hexagonal grid structure. Next, we propose an Ant Colony Optimization (ACO) heuristic to efficiently solve large problem instances. We perform a series of numerical experiments and compare the performance of the exact MILP solution with that of the proposed ACO heuristic.