地面运动目标的多UAV协同搜索方法

对地面运动目标的搜索是无人机(unmanned aerial vehicle, UAV)航路规划的重要研究内容之一,受目标运动的影响,传统的垂线扫描搜索方法对速度较大的运动目标搜索能力不足。为了提升对运动目标的搜索效率,提出多无人机(multi-unmanned aerial vehicle, multi-UAV)并排回寻式搜索方法,以回寻速度与推进距离为参数构建了协同搜索数学模型,搜索效率须在搜索速率和发现概率2个指标之间权衡,通过对模型参数进行优化,得出不同应用场景下的最优搜索方案。仿真结果表明:与垂线扫描搜索法相比,在相同的发现概率下,该方法允许目标的运动速度更快;在目标运动速度相同时,目标发现概率更高。在算例的飞行条件下,目标发现概率比垂线扫描法提高约15个百分点。

Multi-UAV cooperative search method for ground moving targets

The search of ground moving targets is an important research content of unmanned aerial vehicle (UAV) route planning. Because of the motion of the target, the search ability of the traditional vertical scanning method is insufficient. In order to improve the effect of moving target search, an abreast tracing back search method of multiple UAVs is proposed and a collaborative search mathematical model is built taking the back search speed and propulsion distance as parameters. And the search efficiency must be weighed between the two indexes: search speed and discovery probability. By optimizing the model parameters, the optimal search scheme is obtained under different application scenarios. The simulation results show that compared with the vertical scanning search method the optimization strategy allows the target to move faster under the same discovery probability and the optimization strategy has higher discovery probability under the same target moving speed. For the flight condition example, the probability of the target detection of the optimization strategy is about 15 percentage points higher than that of the vertical scanning method.