A Sparse Manifold Learning Approach to Robust Indoor Positioning Based on Wi-Fi RSS Fingerprinting

A Sparse Manifold Learning Approach to Robust Indoor Positioning Based on Wi-Fi RSS Fingerprinting

The emerging location-based applications depend on the fast and accurate positioning of mobile targets. Wi-Fi received signal strength (RSS) fingerprinting provides a promising solution to localize an object in indoor environments. Among the factors challenging the RSS fingerprinting based algorithm...

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Bibliographic Details
Main Authors: Gang Shen, Dan Han, Peiwen Liu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Expectation-maximization
indoor positioning
manifold learning
received signal strength
Online Access:https://ieeexplore.ieee.org/document/8830475/

Internet

https://ieeexplore.ieee.org/document/8830475/

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