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Indoor Smartphone Localization Based on LOS and NLOS Identification.

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  • 1School of Electronics Engineering, Chungbuk National University, Chungbuk 28644, Korea. johj0840@gmail.com.

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|November 21, 2018
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Summary
This summary is machine-generated.

This study introduces an indoor localization method using smartphone signal strength. By distinguishing between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, it significantly reduces distance errors for accurate positioning.

Keywords:
LOS/NLOSWiFiindoor localizationsmartphonetrilateration

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Geomatics Engineering

Background:

  • Global Positioning System (GPS) is vital for location-based services but ineffective indoors.
  • Indoor localization requires alternative techniques like time of arrival, angle of arrival, or signal strength.
  • Existing methods face challenges with accuracy in complex indoor environments.

Purpose of the Study:

  • To propose a novel indoor localization scheme utilizing wireless signal strength on smartphones.
  • To enhance positioning accuracy by addressing distance estimation errors inherent in trilateration.
  • To develop a practical, smartphone-implementable solution for indoor navigation.

Main Methods:

  • Developed an indoor localization algorithm based on signal strength measurements from smartphones.
  • Employed the trilateration method for position estimation.
  • Implemented a novel approach to differentiate between line-of-sight (LOS) and non-line-of-sight (NLOS) propagation paths to refine distance calculations.

Main Results:

  • The proposed algorithm significantly reduced distance estimation errors compared to traditional methods.
  • Line-of-sight (LOS)/non-line-of-sight (NLOS) identification improved the accuracy of distance measurements.
  • The smartphone application demonstrated effective and accurate indoor localization capabilities.

Conclusions:

  • The developed indoor localization scheme offers a practical and accurate solution for smartphones.
  • Distinguishing LOS and NLOS conditions is crucial for improving indoor positioning accuracy.
  • This method provides a viable alternative for location-based services in GPS-denied environments.