Abstract

Fingerprint is a typical indoor-positioning algorithm, which measures the strength of wireless signals and creates a radio map. Using this radio map, the position is estimated through comparisons with the received signal strength measured in real-time. The radio map has a direct effect on the positioning performance; therefore, it should be designed accurately and managed efficiently, according to the type of wireless signal, amount of space, and wireless-signal density. This paper proposes a real-time recursive radio map creation algorithm that combines Wi-Fi and geomagnetism. The proposed method automatically recreates the radio map using geomagnetic radio-map dual processing (GRDP), which reduces the time required to create it. It also reduces the size of the radio map by actively optimizing its dimensions using an entropy-based minimum description length principle (MDLP) method. Experimental results in an actual building show that the proposed system exhibits similar map creation time as a system using a Wi-Fi–based radio map. Geomagnetic radio maps exhibiting over 80% positioning accuracy were created, and the dimensions of the radio map that combined the two signals were found to be reduced by 23.81%, compared to the initially prepared radio map. The dimensions vary according to the wireless signal state, and are automatically reduced in different environments.

Highlights

  • Unlike Time of Flight (TOF)-based ultra-wide band (UWB) and chirp spread spectrum (CSS), which measure signal arrival times, fingerprint is an indoor-positioning technology based on measuring the received signal strength (RSS)

  • This paper proposes a new real-time recursive radio map creation algorithm based on Wi-Fi and geomagnetism

  • This paper proposed a new real-time recursive radio map creation algorithm based on Wi-Fi and geomagnetism

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Summary

Introduction

Unlike Time of Flight (TOF)-based ultra-wide band (UWB) and chirp spread spectrum (CSS), which measure signal arrival times, fingerprint is an indoor-positioning technology based on measuring the received signal strength (RSS). The proposed algorithm automatically creates geomagnetic radio maps by using geomagnetic radio-map dual processing (GRDP) in the training phase, to remove the existing radio map creation processes involving geomagnetic methods that require measurements for each angle and consume a lot of time. Based on this phase, in the positioning phase, the proposed. MDLP-based radio map updating greatly reduces the sizes of the radio maps by actively optimizing their dimensions using the entropy-based minimum description length principle (MDLP) method, rather than the support vector machine (SVM) method that classifies the RSSI

Geomagnetism-Based Fingerprint
Minimum Description Length Principle
Proposed Radio Map Based on Geomagnetic Field and Wi-Fi
Fusion Radio Map Data Acquisition
Creating and Updating the Proposed Radio Map
Experiments and Evaluation
Findings
Conclusions
Full Text
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