Toward location-enabled IoT (LE-IoT): IoT positioning techniques, error sources, and error mitigation

Y Li, Y Zhuang, X Hu, Z Gao, J Hu… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Localization techniques are becoming key to add location context to the Internet-of-Things
(IoT) data without human perception and intervention. Meanwhile, the newly emerged low …

Comprehensive analysis of distance and similarity measures for Wi-Fi fingerprinting indoor positioning systems

J Torres-Sospedra, R Montoliu, S Trilles… - Expert Systems with …, 2015 - Elsevier
Recent advances in indoor positioning systems led to a business interest in those
applications and services where a precise localization is crucial. Wi-Fi fingerprinting based …

Robust pedestrian dead reckoning based on MEMS-IMU for smartphones

J Kuang, X Niu, X Chen - Sensors, 2018 - mdpi.com
This paper proposes a pedestrian dead reckoning (PDR) algorithm based on the strap-down
inertial navigation system (SINS) using the gyros, accelerometers, and magnetometers on …

An improved inertial/wifi/magnetic fusion structure for indoor navigation

Y Li, Y Zhuang, P Zhang, H Lan, X Niu, N El-Sheimy - Information Fusion, 2017 - Elsevier
This paper proposes a dead-reckoning (DR)/WiFi fingerprinting/magnetic matching (MM)
integration structure that uses off-the-shelf sensors in consumer portable devices and …

Tightly-coupled integration of WiFi and MEMS sensors on handheld devices for indoor pedestrian navigation

Y Zhuang, N El-Sheimy - IEEE Sensors Journal, 2015 - ieeexplore.ieee.org
The need for indoor pedestrian navigators is quickly increasing in various applications over
the last few years. However, indoor navigation still faces many challenges and practical …

Indoor positioning based on pedestrian dead reckoning and magnetic field matching for smartphones

J Kuang, X Niu, P Zhang, X Chen - Sensors, 2018 - mdpi.com
This paper presents an ambient magnetic field map-based matching (MM) positioning
algorithm for smartphones in an indoor environment. To improve the low distinguishability of …