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Image Sensor-based Three-dimensional Visible Light Positioning For Various Environments.

Home
Image Sensor-based Three-dimensional Visible Light Positioning For Various Environments.

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Image Sensor-Based Three-Dimensional Visible Light Positioning for Various Environments.

Xiangyu Liu¹, Junqi Zhang¹, Song Song^2,3

¹The School of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, China.

Sensors (Basel, Switzerland)

|August 14, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study introduces a 3D visible light positioning system using image sensors and inertial measurement units (IMU). It achieves high-precision positioning even with a single LED or no light, improving accuracy in diverse environments.

Keywords:

three-dimensional positioning unscented particle filter algorithm visible light positioning

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Area of Science:

Computer Vision
Robotics
Indoor Positioning Systems

Background:

Visible light positioning (VLP) systems using image sensors (IS) are gaining attention.
Current IS-based VLP systems struggle with 2D limitations, reliance on inertial measurement units (IMU), and performance degradation under challenging conditions like single LED or decoding failures.

Purpose of the Study:

To develop a novel three-dimensional (3D) visible light positioning system for enhanced performance across various environments.
To overcome the limitations of existing 2D positioning systems and improve accuracy when LED signals are weak or absent.

Main Methods:

Utilized IMU data to determine the receiver's state and 2D position.
Implemented a height-size curve fitting method to calculate receiver height, avoiding traditional iterative errors.

Developed a firefly-assisted unscented particle filter (FA-UPF) algorithm for robust positioning during LED signal loss or decoding failures.

Main Results:

Achieved a positioning error within 10 cm under a single LED condition.
Demonstrated an average positioning error of 6.45 cm using the FA-UPF algorithm in scenarios with no light source.
The proposed system offers high-precision dynamic positioning capabilities.

Conclusions:

The novel IS-based VLP system effectively addresses limitations of existing methods, providing accurate 3D positioning.
The FA-UPF algorithm significantly enhances positioning reliability and accuracy in challenging, low-light, or signal-absent environments.
This research contributes to more robust and versatile indoor positioning solutions.