Collaborative RF-SLAM for Multipath Channels

Robert M. Tenny, Todd E. Humphreys, Atieh Khamesi, Thomas Cheng, Stefan Adalbjörnsson

Abstract:	This paper presents a collaborative technique for radio-frequency simultaneous localization and mapping (RF-SLAM) for positioning in indoor environments and urban canyons using signals from a single base station. Multipath effects in indoor environments and urban canyons create ambiguities in both the time of arrival (TOA) and angle of arrival (AOA) measurements, causing difficulty for traditional localization methods. Yet reflections can be exploited for positioning by serving as landmarks for RF-SLAM. Multipath components caused by specular reflections are used to aid in positioning by estimating the location of a virtual transmitter (VT) transmitting a signal with the same properties as the reflected signal. The line-of-sight path to the base station and specular reflections are used to jointly estimate the user’s position, velocity, and the position of VTs, enabling robust positioning despite multipath channels. This paper makes three primary contributions. First, it develops the unscented Poisson multi-Bernoulli mixture SLAM (UPMBM-SLAM) estimator to tightly couple TOA and AOA measurements with an inertial sensor to jointly estimate the UE and VT positions and detect walls. Second, it validates the UPMBM-SLAM estimator using data simulated by ray tracing software. Third, it leverages the VT estimates from multiple UEs to create collaborative maps of the VT locations and thereby improve localization precision.
Published in:	Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025) September 8 - 12, 2025 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	1732 - 1747
Cite this article:	Tenny, Robert M., Humphreys, Todd E., Khamesi, Atieh, Cheng, Thomas, Adalbjörnsson, Stefan, "Collaborative RF-SLAM for Multipath Channels," Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 1732-1747. https://doi.org/10.33012/2025.20379
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In