Magicol: Indoor Localization Using Pervasive Magnetic Field and Opportunistic WiFi Sensing

By Yuanchao Shu, Cheng Bo, Guobin Shen, Chunshui Zhao, Liqun Li, Feng Zhao. IEEE Journal on Selected Areas in Communications, 2015

332 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Ocean Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b71aa069fb3ff19d7228b9bbc3b2e766bdf835c0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Pavel Davidson
2. Roger Zimmermann
3. Robert Piché

In Ocean Engineering

1. Pavel Davidson
2. Robert Piché

In Signal Processing

1. Li Cheng
2. Roger Zimmermann
3. Zhenguang Liu
4. Robert Piché
5. Pavel Davidson
6. Qi Liu

Citations in the corpus

• A Survey of Selected Indoor Positioning Methods for Smartphones (2017, background): “This approach has one important advantage that makes it attractive for indoor positioning: the magnetic field is everywhere, it is relatively stable [40]–[42], and consequently no pre-installed infrastructure is required.”
• Fusion of Magnetic and Visual Sensors for Indoor Localization: Infrastructure-Free and More Effective (2017, methodology): “, [1], [4]), 2) Stable Geomagnetic Field: To evaluate the stability of the geomagnetic field across locations, we have measured the magnetic field m at 20 randomly selected locations in three different buildings of NUS (the National University of Singapore).”
• Non-GPS Positioning Systems (2017, unknown): “These include FM [18], CIR [136], UWB [115], and magnetic field [109].”