WiFi-RTT Posterity SLAM for Pedestrian Navigation in Indoor Environments

WiFi has vast infrastructure presence making it an ideal candidate for mobile indoor positioning. WiFi Fine Time Measurement (FTM), is a WiFi protocol that enables the time of flight (ToF) of a WiFi signal to be determined; referred to as WiFi Round Trip Timing (RTT). This has allowed ToF based positioning algorithms to be applied to WiFi signals which could provide an improvement over the established RSSI-based positioning. A common assumption in WiFi RTT research is prior knowledge of the access point locations in an environment. The research in this paper explores the accuracy of WiFi RTT positioning in an indoor environment by utilising a FastSLAM algorithm applied to WiFi RTT that improves over time with the benefit of previous SLAM maps of the environment, this is known as Posterity SLAM. This specific version of the algorithm presents a positioning solution that has sub-two-metre accuracy for the mobile device without the need for a dedicated survey step. In some cases the final horizontal position error of the mobile device was sub-metre. The algorithm was effective at improving the accuracy of landmark estimates for shorter trials 100% of the time. For the landmark estimates, Posterity SLAM achieved sub-two-metre accuracy 78% of the time improving on regular SLAM which achieved sub-two-metre accuracy 61% of the time. The landmark position accuracy was sub-metre 42% of the time for Posterity SLAM and 28% of the time for regular SLAM.

Authors

Publication Details

Journal
Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
Published
2024-10-09
DOI
https://doi.org/10.33012/2024.19877
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

WiFi-RTT Posterity SLAM for Pedestrian Navigation in Indoor Environments

Paul D. Groves, Kiran Raja
Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
Indoor and Outdoor Localization Technologies
article

WiFi-RTT Posterity SLAM for Pedestrian Navigation in Indoor Environments

Paul D. Groves, Kiran Raja
article en

Abstract

WiFi has vast infrastructure presence making it an ideal candidate for mobile indoor positioning. WiFi Fine Time Measurement (FTM), is a WiFi protocol that enables the time of flight (ToF) of a WiFi signal to be determined; referred to as WiFi Round Trip Timing (RTT). This has allowed ToF based positioning algorithms to be applied to WiFi signals which could provide an improvement over the established RSSI-based positioning. A common assumption in WiFi RTT research is prior knowledge of the access point locations in an environment. The research in this paper explores the accuracy of WiFi RTT positioning in an indoor environment by utilising a FastSLAM algorithm applied to WiFi RTT that improves over time with the benefit of previous SLAM maps of the environment, this is known as Posterity SLAM. This specific version of the algorithm presents a positioning solution that has sub-two-metre accuracy for the mobile device without the need for a dedicated survey step. In some cases the final horizontal position error of the mobile device was sub-metre. The algorithm was effective at improving the accuracy of landmark estimates for shorter trials 100% of the time. For the landmark estimates, Posterity SLAM achieved sub-two-metre accuracy 78% of the time improving on regular SLAM which achieved sub-two-metre accuracy 61% of the time. The landmark position accuracy was sub-metre 42% of the time for Posterity SLAM and 28% of the time for regular SLAM.

Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
Sustainable cities and communities
Openalex Percentile: Top 84%
Indoor and Outdoor Localization Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

WiFi-RTT Posterity SLAM for Pedestrian Navigation in Indoor Environments — Paul D. Groves, Kiran Raja · Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM) (2024) | TGRS Research Map | TGRS