Cooperative Detection for Dynamic Marine Targets Based on Improved A-star Algorithm

Cooperative detection strategies are crucial for maritime rescue missions involving dynamic targets, but maximizing detection efficacy is challenging under the operational constraint of limited unmanned system flight time. To address this issue, an improved A-star algorithm is proposed to enhance performance in dynamic target detection. It integrates two core components: 1) a target motion prediction model, employing a Markov process, coupled with an improved A-star path planning logic to proactively guide the search, and 2) a coordination pheromone mechanism fused with artificial potential field constraints to ensure efficient multi-agent coverage and collision avoidance. Simulation results demonstrate that the proposed algorithm achieves substantially superior performance compared to traditional search methods, and also exhibits reduced sensitivity to the initial deployment positions of the unmanned systems, enhancing its operational robustness.