Single-Base-Station NLoS Outdoor Localization via Sequential Radio-Map Matching

Abstract

Accurate outdoor localization in Non-Line-of-Sight (NLoS) environments remains a critical challenge for wireless communication and sensing systems. Existing methods, including positioning based on the Global Navigation Satellite System (GNSS) and triple Base Stations (BSs) techniques, cannot provide reliable performance under NLoS conditions, particularly in dense urban areas with strong multipath effects. To address this limitation, we propose a single BS localization framework that adopts a two-stage design: a Radio Map (RM) is constructed offline as the spatial prior, and the position is estimated online by matching the sequence of signal measurements, against candidate sequences induced from the RM. To evaluate the framework, we build a trajectory-based dataset on top of the RadioMapSeer dataset under short-step and long-step settings. Experimental results show that sequential observations can effectively reduce localization ambiguity, and that the final accuracy depends strongly on radio-map fidelity and trajectory sampling design.