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Maximum Likelihood Indoor Localization of a WiFi Radio Transmitter with Structural Knowledge

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conference contribution
posted on 2024-11-23, 06:27 authored by Shuai Sun, Xuezhi WangXuezhi Wang, William MoranWilliam Moran, Akram HouraniAkram Hourani, Wayne RoweWayne Rowe
In this paper, we present a method for estimating the location of a WiFi transmitter by a receiver using the radio resource and knowledge of the indoor room structure. We derive a three-ray path propagation model for the received radio signal in a known indoor environment. We show that the position of the transmitter could be localized using the received radio signal measurements. The likelihood under this model exhibits multiple local peaks when only few frequencies are used, which leads to the location ambiguities under the Maximum Likelihood criterion. We observed in simulation that the ambiguous locations under the Maximum Likelihood estimation vary with the WiFi radio frequency used but the ground truth location is always presented as a peak. Therefore, we use multiple WiFi frequency bands to resolve the localization ambiguity. A subspace based method is applied in combination with Maximum Likelihood method utilizing the same set of measurements to improve localization efficiency. Simulation using commercial ray tracing software presents promising result.

History

Start page

27

End page

31

Total pages

5

Outlet

Proceedings of the 9th International Conference on Signal Processing Systems 2017

Name of conference

9th International Conference on Signal Processing Systems 2017

Publisher

ACM

Place published

United States

Start date

2017-11-27

End date

2017-11-30

Language

English

Copyright

© 2017 Association for Computing Machinery

Former Identifier

2006082627

Esploro creation date

2020-06-22

Fedora creation date

2018-09-19

Open access

  • Yes

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