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Distributed PLKF using delayed information sharing for 3D AOA target tracking

机译:使用延迟信息共享进行3D AOA目标跟踪的分布式PLKF

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This paper investigates the problem of distributed angle-of-arrival (AOA) target tracking in 3D space using unmanned aerial vehicles (UAVs). Because of communication constraints arising from distance and bandwidth constraints in a distributed UAV system, some UAVs may not be able to share their information with all other UAVs. This will lead to reduced tracking performance. In order to improve the estimation performance, a 3D distributed pseudolinear Kalman filter (DPLKF) using delayed information through intermediate UAVs is proposed. To track a moving target, a new estimation method using 1-step delayed information is developed which has low computational complexity. The communication topology with delayed information sharing is analyzed. In order to reduce communication traffic, a direct neighbors selection strategy is proposed. The effectiveness of the proposed estimation strategy is demonstrated with simulation examples.
机译:本文研究了使用无人机(UAV)在3D空间中进行分布式到达角(AOA)目标跟踪的问题。由于分布式UAV系统中距离和带宽限制引起的通信限制,某些UAV可能无法与所有其他UAV共享其信息。这将导致跟踪性能降低。为了提高估计性能,提出了一种通过中间无人飞行器使用延迟信息的3D分布式伪线性卡尔曼滤波器(DPLKF)。为了跟踪运动目标,开发了一种使用一阶延迟信息的新估计方法,该方法具有较低的计算复杂度。分析了信息共享延迟的通信拓扑。为了减少通信流量,提出了一种直接邻居选择策略。仿真实例证明了所提出的估计策略的有效性。

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