Simultaneous Localization and Mapping in Multipath Environments: Mapping and Reusing of Virtual Transmitters

Abstract

Channel-SLAM is an algorithm which uses multipath propagation for positioning and treats multipath components (MPCs) as line-of-sight (LoS) signals originated from virtual transmitters (VTs). To use the information of the MPCs, Channel-SLAM estimates the receiver position and the position of the VTs simultaneously using simultaneous localization and mapping (SLAM) and does not require any prior information such as room-layout or a database for fingerprinting. This paper investigates mapping, where we derive a probabilistic map representation based on the receiver positions. Thus, if the receiver knows its current location, the information in the probabilistic map helps to estimate the trajectory of further receiver movement. Similar to SLAM approaches, we estimate, map and reuse VT positions in this paper. The algorithm is evaluated based on measurements in an indoor scenario with one fixed transmitter and a moving receiver. We show that indoor positioning is possible with only one transmitter when MPCs are used.