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Blind Cancellation in Radar-Based Self Driving Vehicles

机译:基于雷达的自动驾驶车辆盲目取消

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摘要

Mutual interference among the radar sensors has become a serious concern due to the extensive growth of self driving vehicles (SDV) equipped with such sensors. The problem becomes more severe with the increase in traffic density, where a large number of SDVs gather within the proximity of inter-vehicular radars. Thereby, the number of resources required to maintain the neighbourhood orthogonality increases with traffic density and further leads to the problem of radar blindness. In this paper, we propose a graph-based resource allocation (GRA) scheme to assign resources to the running SDV pool. GRA assures that two closely located SDVs may not simultaneously use the same resource. Also, we integrate the notion of traffic-based dynamic-range approach (TDA) with GRA. Then, through simulation results, it is shown that GRA outperforms the state of art random allocation approach. Further, it is shown that GRA, along with TDA, may eliminate the problem of radar blindness.
机译:由于具有这种传感器的自动驱动车辆(SDV)的广泛增长,雷达传感器之间的相互干扰已经成为一个严重的问题。随着交通密度的增加,问题变得更加严重,其中大量SDV聚集在内的车辆间雷达的附近。因此,维持邻域正交性所需的资源数量随着流量密度而增加,并进一步导致雷达失明的问题。在本文中,我们提出了一种基于图形的资源分配(GRA)方案,用于将资源分配给运行的SDV池。 GRA确保两个密切的SDVS可能不会同时使用相同的资源。此外,我们与GRA集成了基于流量的动态范围方法(TDA)的概念。然后,通过仿真结果,示出了GRA优于艺术随机分配方法的状态。此外,表明GRA以及TDA可以消除雷达失明的问题。

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