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Multiple target tracking by a distributed UWB sensor network based on the PHD filter

机译:基于PHD滤波器的分布式UWB传感器网络的多目标跟踪

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In this paper we describe a method for detection, localization and tracking of multiple non-cooperative moving targets by multiple static ultra-wideband (UWB) radar sensors. The targets are detected using electromagnetic waves backscattered by the target towards the receivers. The sensors consist of two receiving and one transmitting antenna connected to a single UWB module, making the sensors capable of autonomous target localization. Gaussian mixture implementation of the probability hypothesis density (PHD) filter is used for estimating the ranges of the detected targets and fusion of the location estimates provided by each sensor, resulting in refined target tracks. The proposed method is verified in a realistic scenario with three moving persons. The results show that UWB sensors can be used as complimentary technology for multiple moving target tracking.
机译:在本文中,我们描述了一种通过多个静态超宽带(UWB)雷达传感器检测,定位和跟踪多个非合作移动目标的方法。使用由目标向接收器反向散射的电磁波检测目标。传感器由连接到单个UWB模块的两个接收天线和一个发射天线组成,使这些传感器能够进行自主目标定位。概率假设密度(PHD)滤波器的高斯混合实现用于估计检测目标的范围以及每个传感器提供的位置估计的融合,从而形成精确的目标轨迹。所提出的方法在三个动人的现实场景中得到了验证。结果表明,UWB传感器可以用作多种运动目标跟踪的补充技术。

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