Abstract

The last two decades have witnessed significant advances in the field of indoor positioning systems, which have led to technologies with high location precision. However, there still lacks robust meter-level indoor positioning approaches which only rely on in-building communication infrastructures and smartphones. We present STARLIT, a system that enables a single LED beacon to localize smartphones to within sub-meter. As the smartphone camera contains millions of pixels, we create a virtual sensor array with the camera to measure the received signal strength (RSS) of the LED beacon. Different from the existing camera-based approaches, which need to capture images of the LED within a short light-to-camera distance, we utilize the reflection light from the floor. By exploiting the rolling shutter mechanism in the smartphone cameras, we propose a solution to separate the signal layer from the image background and noise. Given the measured RSSs, we establish an equation set with the Lambertian model and the camera projection model to solve the location of the smartphone. We have implemented STARLIT and evaluated its performance in an office room. Our experiments demonstrate that the STARLIT can achieve a median error of 23cm and an 80-percentile error of 55cm.

Highlights

  • Indoor positioning techniques which rely on in-building communication infrastructures and smartphones have attracted much attention from both academia and industry

  • We propose STARLIT, a novel visible light positioning (VLP) system which employs the complementary metal oxide semiconductor (CMOS) cameras built-in smartphones to receive the light signals reflected from the floor

  • 3) STARLIT can work in a further light-to-camera distance without limitation to the camera’s resolution

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Summary

INTRODUCTION

Indoor positioning techniques which rely on in-building communication infrastructures and smartphones have attracted much attention from both academia and industry. LED has many important features which make it suitable for communication infrastructures, including high bandwidth, ‘‘green’’ technology, long lifetime, and costefficient [5] Both the light sensor and the camera on the smartphone are not designed for receiving high frequency optical signals. VISIBLE LIGHT POSITIONING Photodiodes are arguably the most common light sensors used for visible light communications [18] Smartphones lack such equipments built-in, some VLP approaches use custom light sensors that can be plugged into smartphones to receive high frequency optical signals [19], [20]. STARLIT captures the reflection from the floor, and the optical signal can fill the whole image without limitation to the light-to-camera distance. RECEIVED SIGNAL STRENGTH ANALYSIS OF REFLECTIONS Our goal is to estimate the location of a smartphone assuming that we know the location of the LED beacon, the optical channel model and the RSS measurements read from multiple sensors. We introduce how to extract the signal layer and infer the RSSs from the signal layer

IMAGE FORMATION MODEL
SEPARATING SIGNAL LAYER BY CAPTURING TWO DIFFERENT EXPOSURES
RSS MEASUREMENTS
CAMERA PROJECTION
OPTICAL CHANNEL MODEL
POSITIONING ALGORITHM
IMPACT OF AMBIENT LIGHT
VIII. DISCUSSION
CAPTURE SETTINGS
TOWARDS LARGE-SCALE DEPLOYMENT
Findings
CONCLUSION
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