P2pnavi: A System-Level Algorithmic Solution For Highly Accurate Direction Estimation For Infrastructure-Free Indoor Navigation

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.