论文标题
使用超宽带收音机的基于TWR和TDOA的本地化的强大而可扩展的技术
Robust and Scalable Techniques for TWR and TDoA based localization using Ultra Wide Band Radios
论文作者
论文摘要
自动驾驶汽车及其应用的当前趋势表明，在低电池和计算成本下定位的需求越来越大。激光雷达以高计算和功耗的成本提供准确的本地化，这可能对无人机有害。对自动无人机的现代需求，例如无覆盖式无接收器（NPNT）和将无人机限制在走廊上的应用要求基础架构不断确定无人机的位置。超宽带收音机（UWB）满足了此类要求，并提供高精度定位和快速位置更新速率，与LIDAR相比，成本和电池消耗的一小部分，并且在茂密的森林校园或室内环境中，与GPS相比，网络的可用性也更大。我们在本文中介绍了一种新颖的协议和技术，可以使用到达的时间差（TDOA）方法来定位用于此类应用的无人机。这进一步提高了位置更新速率而不牺牲准确性并将其与传统方法进行比较
Current trends in autonomous vehicles and their applications indicates an increasing need in positioning at low battery and compute cost. Lidars provide accurate localization at the cost of high compute and power consumption which could be detrimental for drones. Modern requirements for autonomous drones such as No-Permit-No-Takeoff (NPNT) and applications restricting drones to a corridor require the infrastructure to constantly determine the location of the drone. Ultra Wide Band Radios (UWB) fulfill such requirements and offer high precision localization and fast position update rates at a fraction of the cost and battery consumption as compared to lidars and also have greater network availability than GPS in a dense forested campus or an indoor setting. We present in this paper a novel protocol and technique to localize a drone for such applications using a Time Difference of Arrival (TDoA) approach. This further increases the position update rates without sacrificing on accuracy and compare it to traditional methods
