基于空海异构无人平台的水下目标搜索与跟踪

The marine heterogeneous unmanned systems can effectively enhance the implementation efficiency of complex missions. In this paper, autonomous undersea vehicles(AUVs) and unmanned aerial vehicles(UAVs) were used for searching and tracking unknown underwater targets in offshore waters. First, the underwater target search and tracking mission was described, and the mission was divided into two stages: target search and target tracking, with the objectives of maximizing the total search space of the AUV&UAV system and minimizing the end position error between the AUV and the underwater target, respectively. Then, a cross-domain collaborative search model of the AUV&UAV system was established, and constraints such as detection range and communication distance for AUVs and UAVs in the model were set. Finally, based on the traditional particle swarm optimization algorithm, an adaptive learning factor regulation strategy and an elite preservation strategy were employed for cross-domain collaborative search and tracking path planning, and search and tracking paths were generated. The simulation experiment demonstrates that the heterogeneous AUV&UAV system based on an improved particle swarm optimization algorithm can more efficiently search and track underwater targets.