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IMMGNNF with visibility for multiple maneuvering target tracking

机译:具有可视性的IMMGNNF可进行多个机动目标跟踪

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In this paper, we develop the Interacting Multiple Model (IMM) estimator using the constant velocity, constant acceleration and coordinated turn model set with Global Nearest Neighbour (GNN) filter to track multiple maneuvering targets. The performance of this IMMGNN filter is further enhanced by incorporating a recursion of the probability of target visibility to take into account instances when a target becomes invisible or when it enters an area occluded by physical barriers or limitations of the sensor. Simulation results demonstrate the superior performance of the IMMGNN filter with target visibility incorporated over its original counterpart.
机译:在本文中,我们使用恒定速度,恒定加速度和带全球最近邻居(GNN)滤波器的协调转弯模型集来开发交互式多模型(IMM)估计器,以跟踪多个机动目标。通过合并目标可见性概率的递归,以考虑到目标变得不可见或进入由物理障碍或传感器限制所遮挡的区域时,IMMGNN滤波器的性能得以进一步增强。仿真结果证明了IMMGNN滤波器的优越性能,并结合了目标可见性,优于其原始对应物。

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