通过实测数据动态估算室内定位误差，提升定位系统可靠性。
Dynamic Accuracy Estimation in a Wi-Fi-based Positioning System
- 基于定位算法的实测数据，动态推算定位误差
- 随机森林回归误差最低，平均绝对误差0.72米
- 适合需要实时精度反馈的室内定位应用
本文提出一种动态精度估计方法，通过定位算法所使用的测量结果推导定位误差。该方法在基于Wi-Fi的室内定位系统中进行了实验验证，测试了多种回归方法（线性回归、随机森林、k近邻、神经网络）。其中，随机森林回归表现最佳，平均绝对误差为0.72米，表明该方法可有效实现定位精度的实时评估。
原文摘要 · Abstract (English)
The paper presents a concept of a dynamic accuracy estimation method, in which the localization errors are derived based on the measurement results used by the positioning algorithm. The concept was verified experimentally in a Wi\nobreakdash-Fi based indoor positioning system, where several regression methods were tested (linear regression, random forest, k-nearest neighbors, and neural networks). The highest positioning error estimation accuracy was achieved for random forest regression, with a mean absolute error of 0.72 m.
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