Abstract
Radio-based localization has the potential to provide centimeter-level position information. In this paper we apply joint probabilistic data association to multipath-assisted simultaneous localization and mapping (SLAM) for this purpose. In multipath-assisted localization, position-related information in multipath components (MPCs) is exploited to increase the accuracy and robustness of indoor tracking. Based on a recently introduced loopy belief propagation multipath-assisted localization scheme that performs probabilistic data association jointly with agent state estimation, we build a method for SLAM without using apriori known environment maps. The proposed method is highly accurate and robust in localizing a mobile agent while building up an environment feature map. It scales well in all relevant systems parameters and has a very low computational complexity.
Original language | English |
---|---|
Title of host publication | 2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017 |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 652-658 |
Number of pages | 7 |
ISBN (Electronic) | 9781509015252 |
DOIs | |
Publication status | Published - 29 Jun 2017 |
Event | 2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017 - Paris, France Duration: 21 May 2017 → 25 May 2017 |
Conference
Conference | 2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017 |
---|---|
Country/Territory | France |
City | Paris |
Period | 21/05/17 → 25/05/17 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Hardware and Architecture