Extended FastSLAM Using Cellular Multipath Component Delays and Angular Information

TL;DR

This paper presents an extended FastSLAM algorithm that uses cellular multipath component delays and angles of arrival to accurately localize a vehicle and transmitters in challenging environments, achieving sub-6 meter accuracy.

Contribution

The paper introduces an extended FastSLAM method leveraging MPC delays and AOA from LTE signals for joint vehicle and transmitter localization.

Findings

Vehicle position error less than 6 meters after 530 meters traveled

Significant improvement over proprioception alone

Effective use of cellular multipath information for localization

Abstract

Opportunistic navigation using cellular signals is appealing for scenarios where other navigation technologies face challenges. In this paper, long-term evolution (LTE) downlink signals from two neighboring commercial base stations (BS) are received by a massive antenna array mounted on a passenger vehicle. Multipath component (MPC) delays and angle-of-arrival (AOA) extracted from the received signals are used to jointly estimate the positions of the vehicle, transmitters, and virtual transmitters (VT) with an extended fast simultaneous localization and mapping (FastSLAM) algorithm. The results show that the algorithm can accurately estimate the positions of the vehicle and the transmitters (and virtual transmitters). The vehicle's horizontal position error of SLAM fused with proprioception is less than 6 meters after a traversed distance of 530 meters, whereas un-aided proprioception results in a horizontal error of 15 meters.