Ulmschneider, MarkusMarkusUlmschneiderGentner, ChristianChristianGentnerDammann, ArminArminDammann2021-03-102021-03-102020-04IEEE/ION Position, Location and Navigation Symposium (PLANS 2020)http://hdl.handle.net/11420/9101Channel-SLAM is a multipath assisted positioning algorithm that treats multipath components as line-of-sight (LoS) signals from virtual transmitters. It maps the physical and virtual transmitters' locations simultaneously with estimating the user position with simultaneous localization and mapping (SLAM). Since Channel-SLAM is a relative localization system, the coordinate systems of transmitter maps from different users are subject to an unknown relative rotation and translation. In this paper, we present a new algorithm to estimate this rotation and translation, which we call map matching. Map matching is a requirement for collaborative Channel-SLAM, where users share transmitter maps to improve their positioning performance. Our idea is to augment maps of transmitter locations in Channel-SLAM with knowledge on from which locations there is a LoS condition to a transmitter in order to increase the robustness of map matching. We evaluate our algorithm by simulations in an indoor scenario.enChannel-SLAMcooperative positioningmap matchingsimultaneous localization and mappingConference Paper10.1109/PLANS46316.2020.9110139Other