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A Belief Propagation Algorithm for Multipath-Based SLAM

Leitinger, Erik LU ; Meyer, Florian ; Hlawatsch, Franz ; Witrisal, Klaus ; Tufvesson, Fredrik LU and Win, Moe Z. (2019) In IEEE Transactions on Wireless Communications 18(12). p.5613-5629
Abstract

We present a simultaneous localization and mapping (SLAM) algorithm that is based on radio signals and the association of specular multipath components (MPCs) with geometric features. Especially in indoor scenarios, robust localization from radio signals is challenging due to diffuse multipath propagation, unknown MPC-feature association, and limited visibility of features. In our approach, specular reflections at flat surfaces are described in terms of virtual anchors (VAs) that are mirror images of the physical anchors (PAs). The positions of these VAs and possibly also of the PAs are unknown. We develop a Bayesian model of the SLAM problem and represent it by a factor graph, which enables the use of belief propagation (BP) for... (More)

We present a simultaneous localization and mapping (SLAM) algorithm that is based on radio signals and the association of specular multipath components (MPCs) with geometric features. Especially in indoor scenarios, robust localization from radio signals is challenging due to diffuse multipath propagation, unknown MPC-feature association, and limited visibility of features. In our approach, specular reflections at flat surfaces are described in terms of virtual anchors (VAs) that are mirror images of the physical anchors (PAs). The positions of these VAs and possibly also of the PAs are unknown. We develop a Bayesian model of the SLAM problem and represent it by a factor graph, which enables the use of belief propagation (BP) for efficient marginalization of the joint posterior distribution. The resulting BP-based SLAM algorithm detects the VAs associated with the PAs and estimates jointly the time-varying position of the mobile agent and the positions of the VAs and possibly also of the PAs, thereby leveraging the MPCs in the radio signal for improved accuracy and robustness of agent localization. The algorithm has a low computational complexity and scales well in all relevant system parameters. Experimental results using both synthetic measurements and real ultra-wideband radio signals demonstrate the excellent performance of the algorithm in challenging indoor environments.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
data association, factor graph, message passing, multipath channel, Simultaneous localization and mapping, SLAM, sum-product algorithm
in
IEEE Transactions on Wireless Communications
volume
18
issue
12
article number
8823946
pages
17 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85072627223
ISSN
1536-1276
DOI
10.1109/TWC.2019.2937781
language
English
LU publication?
yes
id
86a8bb37-7278-43a8-a61f-77ed0c6cb050
date added to LUP
2020-05-24 16:43:46
date last changed
2020-09-23 08:10:57
@article{86a8bb37-7278-43a8-a61f-77ed0c6cb050,
  abstract     = {<p>We present a simultaneous localization and mapping (SLAM) algorithm that is based on radio signals and the association of specular multipath components (MPCs) with geometric features. Especially in indoor scenarios, robust localization from radio signals is challenging due to diffuse multipath propagation, unknown MPC-feature association, and limited visibility of features. In our approach, specular reflections at flat surfaces are described in terms of virtual anchors (VAs) that are mirror images of the physical anchors (PAs). The positions of these VAs and possibly also of the PAs are unknown. We develop a Bayesian model of the SLAM problem and represent it by a factor graph, which enables the use of belief propagation (BP) for efficient marginalization of the joint posterior distribution. The resulting BP-based SLAM algorithm detects the VAs associated with the PAs and estimates jointly the time-varying position of the mobile agent and the positions of the VAs and possibly also of the PAs, thereby leveraging the MPCs in the radio signal for improved accuracy and robustness of agent localization. The algorithm has a low computational complexity and scales well in all relevant system parameters. Experimental results using both synthetic measurements and real ultra-wideband radio signals demonstrate the excellent performance of the algorithm in challenging indoor environments.</p>},
  author       = {Leitinger, Erik and Meyer, Florian and Hlawatsch, Franz and Witrisal, Klaus and Tufvesson, Fredrik and Win, Moe Z.},
  issn         = {1536-1276},
  language     = {eng},
  month        = {12},
  number       = {12},
  pages        = {5613--5629},
  publisher    = {IEEE - Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Transactions on Wireless Communications},
  title        = {A Belief Propagation Algorithm for Multipath-Based SLAM},
  url          = {http://dx.doi.org/10.1109/TWC.2019.2937781},
  doi          = {10.1109/TWC.2019.2937781},
  volume       = {18},
  year         = {2019},
}