论文标题
无人机的基于范围的本地化算法中的测量误差：分析和实验
Measurement Errors in Range-Based Localization Algorithms for UAVs: Analysis and Experimentation
论文作者
论文摘要
本地化地面设备（GDS）是多种应用的重要要求，例如基础设施监测，精密农业，搜索和救援行动，仅举几例。为此，由于其灵活性，无人驾驶飞机（无人机）或无人机提供了有前途的技术。但是，使用无人机（本地化程序不可或缺的一部分）进行的距离测量结果会产生几个影响定位精度的错误。在本文中，我们为不同类型的测量误差对无人机和GD之间的地面距离的影响提供了分析表达式。我们回顾了三种基于范围的和三种无范围的定位算法，确定它们的错误源，并通过分析得出由于汇总多个不准确测量结果而导致的错误界限。然后，我们扩展了无范围的算法以提高精度。我们验证了我们的理论分析，并比较了使用十个GDS和一架无人机从测试台收集数据后观察到的算法的定位误差，该数据配备了超宽带（UWB）天线并在开放田中运行。结果表明，我们的分析与实验定位误差非常匹配。此外，与原始同行相比，扩展无范围的算法显着提高了准确性。
Localizing ground devices (GDs) is an important requirement for a wide variety of applications, such as infrastructure monitoring, precision agriculture, search and rescue operations, to name a few. To this end, unmanned aerial vehicles (UAVs) or drones offer a promising technology due to their flexibility. However, the distance measurements performed using a drone, an integral part of a localization procedure, incur several errors that affect the localization accuracy. In this paper, we provide analytical expressions for the impact of different kinds of measurement errors on the ground distance between the UAV and GDs. We review three range-based and three range-free localization algorithms, identify their source of errors, and analytically derive the error bounds resulting from aggregating multiple inaccurate measurements. We then extend the range-free algorithms for improved accuracy. We validate our theoretical analysis and compare the observed localization error of the algorithms after collecting data from a testbed using ten GDs and one drone, equipped with ultra wide band (UWB) antennas and operating in an open field. Results show that our analysis closely matches with experimental localization errors. Moreover, compared to their original counterparts, the extended range-free algorithms significantly improve the accuracy.
