Multipath Assisted Positioning for Pedestrians

Abstract

This paper presents and extends the idea of multipath assisted positioning, named Channel-SLAM. Generally, multipath reception degrades the accuracy of the positioning device as long as the receiver is based on standard methods. Strategies to mitigate multipath effects on range estimates are in general based on the estimation of the channel impulse response (CIR). All these methods have in common that they determine the CIR in order to remove the influence on the estimate of the line-of-sight (LoS) path delay. In contrast, Channel-SLAM uses the multipath propagation of the wireless signal to allow positioning in cases of insufficient number of transmitters or increase the accuracy otherwise. Channel-SLAM treats multipath components (MPCs) as signals from virtual transmitters (VTs) which are time synchronized to the physical transmitter and fixed in their position. To use the information of the MPCs, Channel-SLAM estimates the user position and the position of the VTs simultaneously and does not require any prior information such as room-layout or a database for fingerprinting. This paper investigates Channel-SLAM for pedestrian navigation. For Channel-SLAM it is essential to obtain angle of arrival (AoA) information for each MPC in order to estimate the VT positions. However, obtaining AoA information in mobile receivers like smartphones is difficult in most of the cases. Hence, the paper uses the heading information of an inertial measurement unit (IMU) to omit the AoA information and to improve the accuracy of Channel-SLAM. The algorithm is evaluated based on measurements with a moving pedestrian and one fixed transmitter. These evaluations demonstrate the concept of Channel-SLAM. We show, that Channel-SLAM is able to determine VT positions accurately. Furthermore, we show that accurate position estimation is possible without the knowledge of the physical transmitter position by using MPCs and the heading information of an IMU. The only conditions to be fulfilled are the presence of a multipath environment, a moving receiver equipped with an IMU as well as an initial prior knowledge of the receiver states, i.e. position and moving direction.