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提出了一种基于贝叶斯滤波器和适航地图的跟踪算法(BF-Hmap),解决间断观测下的无人机地面目标跟踪问题.采用基于中心线和梯度图的快速道路提取算法生成目标适航地图,该图描述了地面目标与当前地形相关的运动能力.采用贝叶斯滤波器分两步在线更新目标状态的后验概率分布,即在预测阶段考虑适航地图对目标运动的约束,以及在估计阶段充分利用目标的所有观测信息.仿真结果表明,在间断观测下该算法对地面机动目标有着良好的跟踪效果.
A tracking algorithm based on Bayesian filter and airworthiness map (BF-Hmap) is proposed to solve the problem of UAV ground target tracking under intermittent observation.A fast path extraction algorithm based on centerline and gradient graph is used to generate target Airworthiness map, which describes the ground target related to the current terrain motion capability.Bayesian filter used to update the target state posterior probability distribution in two steps, that is, in the prediction phase to consider the air map constraints on the target motion , And all the observation information which make full use of the target in the estimation stage.The simulation results show that the algorithm has a good tracking effect on the ground maneuvering target under the intermittent observation.