Route Optimization of on Call Submarine Search Based on Genetic Algorithm

Abstract

To address the situation wherein an enemy submarine maneuvers in an unknown course when an anti-submarine surface ship is called, a genetic algorithm-based submarine search method is proposed. The method combines the ship sonar detection model, enemy submarine target motion model, ship search motion model, and search path discovery probability calculation model. It introduces information confidence into the discovery probability calculation model, which enhances its reliability. Subsequently, a genetic algorithm is used to solve the optimal heading angle and speed of each section of a single ship and double ships in the on-call search process, and the optimal paths of single and double ships on call spiral search are determined. Finally, the variation law of the discovery probability of searching the target is formulated under the conditions of changing only the heading angle and changing both the angle and speed of single and double ships. The results indicate that, compared to the traditional spiral algorithm, the ship search mechanism with increasing change speed is more flexible and can improve the discovery probability. When the search force is sufficient, using a multiship formation search can significantly improve the discovery probability. The results provide a tactical reference for surface ship searches and submarine attacks.

Keywords

• on call search
• surface ship
• spiral search
• genetic algorithm
• discovery probability