Indoor positioning system designs using visible LED lights: performance comparison of TDM and FDM protocols

2015 ◽  
Vol 51 (1) ◽  
pp. 72-74 ◽  
Author(s):  
U. Nadeem ◽  
N.U. Hassan ◽  
M.A. Pasha ◽  
C. Yuen
Keyword(s):  
Indoor Positioning ◽  
Performance Comparison ◽  
Positioning System ◽  
Led Lights ◽  
Indoor Positioning System ◽  
System Designs

scholarly journals Indoor Positioning System using LED Lights and a Dual Image Sensor

2015 ◽  
Vol 19 (6) ◽  
pp. 586-591 ◽  
Author(s):  
Myoung-geun Moon ◽  
Su-il Choi ◽  
Jaehyung Park ◽  
Jin Young Kim
Keyword(s):  
Indoor Positioning ◽  
Image Sensor ◽  
Positioning System ◽  
Dual Image ◽  
Led Lights ◽  
Indoor Positioning System

Highly accurate 3D wireless indoor positioning system using white LED lights

2014 ◽  
Vol 50 (11) ◽  
pp. 828-830 ◽  
Author(s):  
U. Nadeem ◽  
N.U. Hassan ◽  
M.A. Pasha ◽  
C. Yuen
Keyword(s):  
Indoor Positioning ◽  
Positioning System ◽  
White Led ◽  
Led Lights ◽  
Indoor Positioning System

scholarly journals A Survey of Smartphone-Based Indoor Positioning System Using RF-Based Wireless Technologies

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7230
Author(s):  
Santosh Subedi ◽  
Jae-Young Pyun
Keyword(s):  
Indoor Localization ◽  
Indoor Positioning ◽  
Performance Comparison ◽  
Location Based Services ◽  
Global Navigation Satellite Systems ◽  
Smart Devices ◽  
Positioning System ◽  
Localization Accuracy ◽  
Satellite Systems ◽  
Indoor Positioning System

In recent times, social and commercial interests in location-based services (LBS) are significantly increasing due to the rise in smart devices and technologies. The global navigation satellite systems (GNSS) have long been employed for LBS to navigate and determine accurate and reliable location information in outdoor environments. However, the GNSS signals are too weak to penetrate buildings and unable to provide reliable indoor LBS. Hence, GNSS’s incompetence in the indoor environment invites extensive research and development of an indoor positioning system (IPS). Various technologies and techniques have been studied for IPS development. This paper provides an overview of the available smartphone-based indoor localization solutions that rely on radio frequency technologies. As fingerprinting localization is mostly accepted for IPS development owing to its good localization accuracy, we discuss fingerprinting localization in detail. In particular, our analysis is more focused on practical IPS that are realized using a smartphone and Wi-Fi/Bluetooth Low Energy (BLE) as a signal source. Furthermore, we elaborate on the challenges of practical IPS, the available solutions and comprehensive performance comparison, and present some future trends in IPS development.

scholarly journals High-Precision RTT-Based Indoor Positioning System Using RCDN and RPN

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3701
Author(s):  
Ju-Hyeon Seong ◽  
Soo-Hwan Lee ◽  
Won-Yeol Kim ◽  
Dong-Hoan Seo
Keyword(s):  
High Precision ◽  
Distance Estimation ◽  
Sampling Period ◽  
Multipath Fading ◽  
Indoor Positioning ◽  
Positioning System ◽  
Positioning Systems ◽  
Positioning Errors ◽  
Location Determination ◽  
Indoor Positioning System

Wi-Fi round-trip timing (RTT) was applied to indoor positioning systems based on distance estimation. RTT has a higher reception instability than the received signal strength indicator (RSSI)-based fingerprint in non-line-of-sight (NLOS) environments with many obstacles, resulting in large positioning errors due to multipath fading. To solve these problems, in this paper, we propose high-precision RTT-based indoor positioning system using an RTT compensation distance network (RCDN) and a region proposal network (RPN). The proposed method consists of a CNN-based RCDN for improving the prediction accuracy and learning rate of the received distances and a recurrent neural network-based RPN for real-time positioning, implemented in an end-to-end manner. The proposed RCDN collects and corrects a stable and reliable distance prediction value from each RTT transmitter by applying a scanning step to increase the reception rate of the TOF-based RTT with unstable reception. In addition, the user location is derived using the fingerprint-based location determination method through the RPN in which division processing is applied to the distances of the RTT corrected in the RCDN using the characteristics of the fast-sampling period.

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