IMU-Aided Motion Compensation of RSS Measurements for Dynamic Visible Light-Inertial Localization

Abstract

Visible Light Positioning (VLP) offers high-precision indoor positioning using existing LED infrastructure. However, in VLP systems using Photodiodes (PDs) as receivers, rapid movement of the PD causes measurement inaccuracies as the Discrete Fourier Transform (DFT) processing yields averaged rather than instantaneous Received Signal Strength (RSS) values. To address this challenge, we propose an RSS correction algorithm that integrates Inertial Measurement Unit (IMU) data with VLP observations to compensate for motion-induced distortions. Our approach leverages IMU-derived motion parameters to model the temporal variation of optical signals during the DFT window, enabling instantaneous RSS estimation. The algorithm is embedded within both tightly and simply coupled VLP/INS integration frameworks that estimate the pose of the moving receiver. This work targets highly dynamic indoor navigation. Simulations validate the correction model, and total-station-tracked experiments confirm reduced RSS discrepancies against model references. Across eight held-out high-dynamic handheld trials with peak translational and angular speeds of 2.25 m/s and 284 deg/s, correction reduces the pooled 3D position and PD-normal inclination root mean square errors relative to the LiDAR/IMU reference with a shared IMU by 56.0% and 71.9%, respectively. Both datasets and source code are publicly available.