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Direction-Based Modified Particle Filter for Vehicle Tracking

机译:基于方向的改进型粒子过滤器用于车辆跟踪

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摘要

This research proposes a modified particle filter to increase the accuracy of vehicle tracking in a noisy and occluded medium. In our proposed method for vehicle tracking, the direction angle of a target vehicle is calculated. The angular difference between the motion direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted depending on their angular distance to the motion direction. Those particles moving in a direction similar to that of the target vehicle are assigned larger weights; this, in turn, increases their probability in a given likelihood function (part of the process of estimation of a target's state parameters). The proposed method is compared against a condensation algorithm. Our results show that the proposed method improves the stability of a particle filter tracker and decreases the particle consumption.
机译:这项研究提出了一种改进的粒子滤波器,以提高在嘈杂和被遮挡的介质中车辆跟踪的准确性。在我们提出的车辆跟踪方法中,计算目标车辆的方向角。观察目标车辆的运动方向与颗粒过滤器的每个颗粒之间的角度差。根据粒子到运动方向的角距离对粒子进行过滤和加权。沿与目标车辆的方向相似的方向移动的那些粒子将被分配较大的权重。反过来,这会增加它们在给定似然函数中的概率(目标状态参数估算过程的一部分)。将该方法与缩合算法进行了比较。我们的结果表明,该方法提高了粒子过滤器跟踪器的稳定性,并减少了粒子消耗。

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