scholarly journals A SOCP-Based Automatic Visual Fingerprinting Method for Indoor Localization System

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 72862-72871
Author(s):  
Xiliang Yin ◽  
Lin Ma ◽  
Xuezhi Tan ◽  
Danyang Qin
Keyword(s):  
Indoor Localization ◽  
Localization System ◽  
Fingerprinting Method

scholarly journals Accurate and Low-Complexity Auto-Fingerprinting for Enhanced Reliability of Indoor Localization Systems

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5346
Author(s):  
Elias Hatem ◽  
Sergio Fortes ◽  
Elizabeth Colin ◽  
Sara Abou-Chakra ◽  
Jean-Marc Laheurte ◽  
...  
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Localization ◽  
Cost Effective ◽  
Low Complexity ◽  
Propagation Model ◽  
Cumulative Distribution ◽  
Navigation Systems ◽  
Localization System ◽  
Fingerprinting Method ◽  
Two Stages

Indoor localization is one of the most important topics in wireless navigation systems. The large number of applications that rely on indoor positioning makes advancements in this field important. Fingerprinting is a popular technique that is widely adopted and induces many important localization approaches. Recently, fingerprinting based on mobile robots has received increasing attention. This work focuses on presenting a simple, cost-effective and accurate auto-fingerprinting method for an indoor localization system based on Radio Frequency Identification (RFID) technology and using a two-wheeled robot. With this objective, an assessment of the robot’s navigation is performed in order to investigate its displacement errors and elaborate the required corrections. The latter are integrated in our proposed localization system, which is divided into two stages. From there, the auto-fingerprinting method is implemented while modeling the tag-reader link by the Dual One Slope with Second Order propagation Model (DOSSOM) for environmental calibration, within the offline stage. During the online stage, the robot’s position is estimated by applying DOSSOM followed by multilateration. Experimental localization results show that the proposed method provides a positioning error of 1.22 m at the cumulative distribution function of 90%, while operating with only four RFID active tags and an architecture with reduced complexity.

Design of a Bell-Shaped Ultra Wideband Antenna for Indoor Localization System

2015 ◽  
Vol 5 (6) ◽  
pp. 323 ◽  
Author(s):  
Nadia Ghariani ◽  
Mohamed Salah Karoui ◽  
Mondher Chaoui ◽  
Mongi Lahiani ◽  
Hamadi Ghariani
Keyword(s):  
Indoor Localization ◽  
Ultra Wideband ◽  
Localization System ◽  
Wideband Antenna

scholarly journals An Indoor Localization System Using Residual Learning with Channel State Information

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 574
Author(s):  
Chendong Xu ◽  
Weigang Wang ◽  
Yunwei Zhang ◽  
Jie Qin ◽  
Shujuan Yu ◽  
...  
Keyword(s):  
Channel State Information ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Location Based Services ◽  
Channel State ◽  
State Information ◽  
Localization Accuracy ◽  
Localization System ◽  
Increasing Demand ◽  
Degradation Problem

With the increasing demand of location-based services, neural network (NN)-based intelligent indoor localization has attracted great interest due to its high localization accuracy. However, deep NNs are usually affected by degradation and gradient vanishing. To fill this gap, we propose a novel indoor localization system, including denoising NN and residual network (ResNet), to predict the location of moving object by the channel state information (CSI). In the ResNet, to prevent overfitting, we replace all the residual blocks by the stochastic residual blocks. Specially, we explore the long-range stochastic shortcut connection (LRSSC) to solve the degradation problem and gradient vanishing. To obtain a large receptive field without losing information, we leverage the dilated convolution at the rear of the ResNet. Experimental results are presented to confirm that our system outperforms state-of-the-art methods in a representative indoor environment.

Acoustic indoor-localization system for smart phones

2014 ◽  
Author(s):  
Fabian Hoflinger ◽  
Joachim Hoppe ◽  
Rui Zhang ◽  
Alexander Ens ◽  
Leonhard Reindl ◽  
...  
Keyword(s):  
Indoor Localization ◽  
Smart Phones ◽  
Localization System
Sign in / Sign up

Export Citation Format

Share Document