Absolute position accuracy is the key performance criterion of an Indoor Localization System (ILS). Since ILS are heterogeneous and complex cyber-physical systems, the localization accuracy depends on various influences from the environment, system configuration, and the application processes. To determine the position accuracy of a system in a reproducible, comparable, and realistic manner, these factors must be taken into account. We propose a strategy for analyzing the influences on the position accuracy of ILS using decision trees in combination with application-related or technology-related categorization. The proposed strategy is validated using empirical data from 120 experiments. The accuracy of an Ultra-Wideband and a LiDAR-based ILS was determined under different application-driven influencing factors, considering the application of autonomous mobile robots in warehouses. Finally, the opportunities and limitations of analyzing decision trees to compare system performance, find a suitable system, optimize the environment or system configuration, and understand the relevance of different influencing factors are presented.

翻译：绝对位置准确性是室内本地化系统(ILS)的主要性能标准。由于ILS是多种复杂的网络物理系统,因此本地化准确性取决于环境、系统配置和应用过程的各种影响。为了以可复制、可比和现实的方式确定系统的位置准确性,必须考虑到这些因素。我们提出了一个战略,用与应用相关或与技术有关的分类相结合的决策树来分析对ILS定位准确性的影响。拟议战略是利用120个实验的经验数据加以验证的。超双频带和基于LIDAR的ILS的准确性是在不同的应用影响因素下确定的,考虑在仓库中应用自主移动机器人。最后,提出了分析决策树以比较系统性能、找到合适的系统、优化环境或系统配置的机会和局限性,并理解不同影响因素的相关性。