Peer-to-peer (P2P) direction estimation based on rotary (TOA) ranging is an effective method for infrastructure-free navigation in indoor environments, which is crucial to first responders, especially firefighters. With the sequential measured distances and corresponding azimuth angles, P2P direction estimation can be defined as a sequence matching problem. This article presents P2PNavi, a system-level algorithmic solution, to overcome the impact of unavoidable indoor ranging error on the matching accuracy. By means of novel preprocessing and matching algorithms, P2PNavi can effectively improve the signal-to-noise ratio (SNR) of the measured sequence and reduce the direction estimation error. The solution is verified by experiments with commercially available TOA devices in a typical office building. P2PNavi significantly outperforms nonsystem-level methods in terms of the root mean square error of direction estimation.

中文翻译：

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P2PNavi：用于无基础设施室内导航的高精度方向估计的系统级算法解决方案

基于旋转 (TOA) 测距的点对点 (P2P) 方向估计是室内环境中无基础设施导航的有效方法，这对急救人员，尤其是消防员至关重要。通过连续测量的距离和相应的方位角，P2P 方向估计可以定义为序列匹配问题。本文介绍了 P2PNavi，一种系统级算法解决方案，以克服不可避免的室内测距误差对匹配精度的影响。P2PNavi通过新颖的预处理和匹配算法，可以有效提高被测序列的信噪比（SNR），降低方向估计误差。该解决方案已通过在典型办公楼中使用商用 TOA 设备进行的实验验证。