Indoor positioning using GPS transmitters: Experimental results

2010 ◽  
Author(s):  
Anca Fluerasu ◽  
A. Vervisch-Picois ◽  
G. Boiero ◽  
G. Ghinamo ◽  
P. Lovisolo ◽  
...  
Keyword(s):  
Indoor Positioning ◽  
Experimental Results

scholarly journals An Indoor AC Magnetic Positioning System

2021 ◽  
Author(s):  
Paolo Carbone ◽  
Guido De Angelis ◽  
Valter Pasku ◽  
Alessio De Angelis ◽  
Marco Dionigi ◽  
...  
Keyword(s):  
Indoor Environment ◽  
Indoor Positioning ◽  
Experimental Results ◽  
System Level ◽  
Line Of Sight ◽  
Positioning System ◽  
Positioning Error ◽  
Geometric Configurations ◽  
Indoor Positioning System ◽  
Non Line Of Sight

<div><div><div><p>This paper describes the design and realization of a Magnetic Indoor Positioning System. The system is entirely realized using off-the-shelf components and is based on inductive coupling between resonating coils. Both system-level architecture and realization details are described along with experimental results. The realized system exhibits a maximum positioning error of less than 10 cm in an indoor environment over a 3×3 m2 area. Extensive experiments in larger areas, in non-line-of-sight conditions, and in unfavorable geometric configurations, show sub-meter accuracy, thus validating the robustness of the system with respect to other existing solutions.</p></div></div></div>

scholarly journals Integration of Convolutional Neural Network and Error Correction for Indoor Positioning

2020 ◽  
Vol 9 (2) ◽  
pp. 74
Author(s):  
Eric Hsueh-Chan Lu ◽  
Jing-Mei Ciou
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Error Correction ◽  
Spatial Information ◽  
Rapid Development ◽  
Indoor Positioning ◽  
Experimental Results ◽  
Global Navigation Satellite Systems ◽  
Signal Interference ◽  
Position Vector

With the rapid development of surveying and spatial information technologies, more and more attention has been given to positioning. In outdoor environments, people can easily obtain positioning services through global navigation satellite systems (GNSS). In indoor environments, the GNSS signal is often lost, while other positioning problems, such as dead reckoning and wireless signals, will face accumulated errors and signal interference. Therefore, this research uses images to realize a positioning service. The main concept of this work is to establish a model for an indoor field image and its coordinate information and to judge its position by image eigenvalue matching. Based on the architecture of PoseNet, the image is input into a 23-layer convolutional neural network according to various sizes to train end-to-end location identification tasks, and the three-dimensional position vector of the camera is regressed. The experimental data are taken from the underground parking lot and the Palace Museum. The preliminary experimental results show that this new method designed by us can effectively improve the accuracy of indoor positioning by about 20% to 30%. In addition, this paper also discusses other architectures, field sizes, camera parameters, and error corrections for this neural network system. The preliminary experimental results show that the angle error correction method designed by us can effectively improve positioning by about 20%.

scholarly journals Universal and Effective Decoding Scheme for Visible Light Positioning Based on Optical Camera Communication

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1925
Author(s):  
Hongzhan Song ◽  
Shangsheng Wen ◽  
Chen Yang ◽  
Danlan Yuan ◽  
Weipeng Guan
Keyword(s):  
Visible Light ◽  
Mobile Devices ◽  
Environmental Changes ◽  
Indoor Positioning ◽  
Image Sensor ◽  
Experimental Results ◽  
Threshold Scheme ◽  
Transmission Channel ◽  
Decoding Algorithm ◽  
Optical Camera Communication

As a promising approach to implement indoor positioning, visible light positioning (VLP) based on optical camera communication (OCC) image sensor has attracted substantial attention. However, the decoding schemes of existing VLP systems still face many challenges. First, the transmission channel between transmitters and receivers can be easily affected by environmental changes, resulting in poor thresholding performance. Second, the inherently unsynchronized air transmission channel issue remains a big obstacle for decoding data. The above two problems limit the application of VLP systems, where various mobile devices are used as receivers and the properties of transmission channel are constantly changing with the movement of receivers. In this paper, a universal and effective decoding scheme named pixel-to-bit calculation (PBC) decoding algorithm for VLP systems is proposed and experimentally demonstrated. It includes a Staged Threshold Scheme which provides excellent thresholding performance for different transmission channel conditions, as well as a Synchronous Decoding Operation to automatically synchronize the clock between transmitters and receivers. A decoding rate of 95.62% at the height of 2.73 m is realized in a practical Robotic-based VLP system embedded with our proposed PBC decoding scheme. In addition, experimental results show that the average decoding rate of the proposed PBC decoding scheme reaches 99.9% when applying different transmitters and receivers.

scholarly journals An Indoor AC Magnetic Positioning System

2021 ◽  
Author(s):  
Paolo Carbone ◽  
Guido De Angelis ◽  
Valter Pasku ◽  
Alessio De Angelis ◽  
Marco Dionigi ◽  
...  
Keyword(s):  
Indoor Environment ◽  
Indoor Positioning ◽  
Experimental Results ◽  
System Level ◽  
Line Of Sight ◽  
Positioning System ◽  
Positioning Error ◽  
Geometric Configurations ◽  
Indoor Positioning System ◽  
Non Line Of Sight

<div><div><div><p>This paper describes the design and realization of a Magnetic Indoor Positioning System. The system is entirely realized using off-the-shelf components and is based on inductive coupling between resonating coils. Both system-level architecture and realization details are described along with experimental results. The realized system exhibits a maximum positioning error of less than 10 cm in an indoor environment over a 3×3 m2 area. Extensive experiments in larger areas, in non-line-of-sight conditions, and in unfavorable geometric configurations, show sub-meter accuracy, thus validating the robustness of the system with respect to other existing solutions.</p></div></div></div>

scholarly journals GEOMAGNETIC FIELD-BASED INDOOR POSITIONING USING BACK-PROPAGATION NEURAL NETWORKS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 557-563
Author(s):  
K. Y. Qiu ◽  
H. Huang ◽  
A. El-Rabbany
Keyword(s):  
Neural Network ◽  
Prediction Models ◽  
Indoor Localization ◽  
Back Propagation ◽  
Weighted Average ◽  
Back Propagation Neural Network ◽  
Indoor Positioning ◽  
Experimental Results ◽  
Positioning Error ◽  
Main Research

Abstract. High-precision indoor positioning in complex environments has always been a hot research topic within the positioning and robotic communities. As one of the indoor positioning technologies, geomagnetic positioning is receiving widespread attention due to its global coverage. Additionally, geomagnetic positioning does not require special infrastructure configuration, its hardware cost is low, and its positioning errors do not accumulate over time. However, geomagnetic positioning is prone to mismatching, which causes serious problems at the positioning points. To tackle this challenge, this paper proposes an indoor localization method based on spectral clustering and weighted back-propagation neural network. The main research contribution is that in the offline phase, the spatial specificity of geomagnetism is used to define the similarity between fingerprints. In addition, a clustering-based reference point algorithm is proposed to divide the sub-fingerprint database, and a positioning prediction model based on back-propagation neural network is trained. Subsequently, in the online stage, the weights of different positioning prediction models are calculated according to the defined fingerprint similarity, weighted average prediction coordinates are obtained, and thereby the positioning accuracy is improved. Experimental results show that, in comparison with other neural network-based positioning methods, the positioning error of our proposed algorithm is reduced by approximately 26.6% and the positioning time is reduced by 24.7%. Experimental results show that the average positioning error of the algorithm is 1.81m.

Diagnostics of Gold Laser Plasmas

1988 ◽  
Vol 102 ◽  
pp. 357-360
Author(s):  
J.C. Gauthier ◽  
J.P. Geindre ◽  
P. Monier ◽  
C. Chenais-Popovics ◽  
N. Tragin ◽  
...  
Keyword(s):  
Experimental Results ◽  
Pure Gold ◽  
Electronic Temperature ◽  
X Ray ◽  
Laser Plasmas ◽  
Collisional Radiative Model ◽  
Radiative Model

AbstractIn order to achieve a nickel-like X ray laser scheme we need a tool to determine the parameters which characterise the high-Z plasma. The aim of this work is to study gold laser plasmas and to compare experimental results to a collisional-radiative model which describes nickel-like ions. The electronic temperature and density are measured by the emission of an aluminium tracer. They are compared to the predictions of the nickel-like model for pure gold. The results show that the density and temperature can be estimated in a pure gold plasma.

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