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Mobile Information Systems
Volume 2017 (2017), Article ID 9170746, 18 pages
Research Article

Positioning Using Terrestrial Multipath Signals and Inertial Sensors

German Aerospace Center (DLR), Institute of Communications and Navigation, Oberpfaffenhofen, 82234 Weßling, Germany

Correspondence should be addressed to Christian Gentner

Received 24 February 2017; Revised 15 June 2017; Accepted 20 July 2017; Published 2 October 2017

Academic Editor: Ruizhi Chen

Copyright © 2017 Christian Gentner et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper extends an algorithm that exploits multipath propagation for position estimation of mobile receivers named Channel-SLAM. Channel-SLAM treats multipath components (MPCs) as signals from virtual transmitters (VTs) and estimates the positions of the VTs simultaneously with the mobile receiver positions. For Channel-SLAM it is essential to obtain angle of arrival (AoA) measurements for each MPC in order to estimate the VT positions. In this paper, we propose a novel Channel-SLAM implementation based on particle filtering which fuses heading information of an inertial measurement unit (IMU) to omit AoA measurements and to improve the position accuracy. Interpreting all MPCs as signals originated from VTs, Channel-SLAM enables positioning also in non-line-of-sight situations. Furthermore, we propose a method to dynamically adapt the number of particles which significantly reduces the computational complexity. A posterior Cramér-Rao lower bound for Channel-SLAM is derived which incorporates the heading information of the inertial measurement unit (IMU). We evaluate the proposed algorithm based on measurements with a single fixed transmitter and a moving pedestrian carrying the receiver and the IMU. The evaluations show that accurate position estimation is possible without the knowledge of the physical transmitter position by exploiting MPCs and the heading information of an IMU.