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On using a Low-Density Flash Lidar for Tracking Closely Spaced Road Vehicles

机译:使用低密度闪光激光雷达跟踪紧密间隔的道路车辆

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This paper focuses on developing an algorithm for tracking closely-spaced road vehicles using a low-density flash lidar. Low-density flash lidars have poor spatial resolution that can causes detections from multiple targets to be merged/unresolved when the targets being tracked are closely spaced. Previous solutions for target tracking with unresolved measurements have typically focused on tracking with exactly two targets with a radar. In this paper, a novel solution based on Probability Density Function (PDF) truncation of the target states is presented to handle the unresolved measurement problem with more than two road targets. The solution proposed can work with a computationally inexpensive data association algorithm and requires no sensor modeling. For illustration, the proposed algorithm is evaluated using simulations for a three target tracking scenario in MATLAB, and the results show that the proposed algorithm can reliably maintain tracks of multiple targets even when the detections are unresolved.
机译:本文侧重于使用低密度闪光激光雷达开发一种用于跟踪紧密间隔的道路车辆的算法。低密度闪光灯段具有较差的空间分辨率,可以在跟踪的目标紧密间隔时导致从多个目标的检测到才能合并/未解决。以未解决的测量的目标跟踪的先前解决方案通常集中在用雷达的两个目标恰好跟踪。本文提出了一种基于概率密度函数(PDF)截断目标状态的新型解决方案,以处理具有两个以上的道路靶标的未解决的测量问题。提出的解决方案可以使用计算廉价的数据关联算法,并且不需要传感器建模。出于说明,使用MATLAB中的三个目标跟踪场景进行评估所提出的算法,结果表明,即使当检测未解决),所提出的算法也可以可靠地维持多个目标的曲目。

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