RAPOSI: Rapidly Installable Positioning System for Indoor Environments

2005 ◽  
pp. 344-353 ◽  
Author(s):  
Florian Schreiner ◽  
Holger Ziemek
Keyword(s):  
Positioning System ◽  
Indoor Environments

UWB Positioning Systsem Design: Selection of Modulation and Multiple Access Schemes

2007 ◽  
Vol 61 (1) ◽  
pp. 45-62 ◽  
Author(s):  
Hui Yu ◽  
Enrique Aguado ◽  
Gary Brodin ◽  
John Cooper ◽  
David Walsh ◽  
...  
Keyword(s):  
Multiple Access ◽  
High Performance ◽  
Ultra Wideband ◽  
Good Time ◽  
Modulation Scheme ◽  
Positioning System ◽  
Indoor Environments ◽  
Signal Design ◽  
Positioning Systems ◽  
Design Selection

In densely-populated cities or indoor environments, limited visibility to satellites and severe multipath effects significantly affect the accuracy and reliability of satellite-based positioning systems. To meet the needs of “seamless navigation” in these challenging environments an advanced terrestrial positioning system is under development. This system is based upon Ultra-Wideband (UWB) technology, which is a promising candidate for this application due to good time domain resolution and immunity to multipath. This paper presents a detailed analysis of two key aspects of the UWB signal design that will allow it to be used as the basis of such a high performance positioning system: the modulation scheme and the multiple access technique. These two aspects are evaluated in terms of spectral efficiency and synchronisation performance over multipath channels. Thus this paper identifies optimal modulation and multiple access techniques for a long range, high performance terrestrial positioning system using UWB.

scholarly journals Induced Magnetic Field-Based Indoor Positioning System for Underwater Environments

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2218
Author(s):  
Sizhen Bian ◽  
Peter Hevesi ◽  
Leif Christensen ◽  
Paul Lukowicz
Keyword(s):  
Magnetic Field ◽  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Wide Band ◽  
Propagation Delay ◽  
Positioning System ◽  
Indoor Environments ◽  
Coverage Area ◽  
Underwater Positioning ◽  
Similar Accuracy

Autonomous underwater vehicles (AUV) are seen as an emerging technology for maritime exploration but are still restricted by the availability of short range, accurate positioning methods necessary, e.g., when docking remote assets. Typical techniques used for high-accuracy positioning in indoor use case scenarios, such as systems using ultra-wide band radio signals (UWB), cannot be applied for underwater positioning because of the quick absorption of the positioning medium caused by the water. Acoustic and optic solutions for underwater positioning also face known problems, such as the multi-path effects, high propagation delay (acoustics), and environmental dependency. This paper presents an oscillating magnetic field-based indoor and underwater positioning system. Unlike those radio wave-based positioning modalities, the magnetic approach generates a bubble-formed magnetic field that will not be deformed by the environmental variation because of the very similar permeability of water and air. The proposed system achieves an underwater positioning mean accuracy of 13.3 cm in 2D and 19.0 cm in 3D with the multi-lateration positioning method and concludes the potential of the magnetic field-based positioning technique for underwater applications. A similar accuracy was also achieved for various indoor environments that were used to test the influence of cluttered environment and of cross environment. The low cost and power consumption system is scalable for extensive coverage area and could plug-and-play without pre-calibration.

scholarly journals Leveraging Visual Place Recognition to Improve Indoor Positioning with Limited Availability of WiFi Scans

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3657 ◽  
Author(s):  
Michał R. Nowicki ◽  
Piotr Skrzypczyński
Keyword(s):  
Indoor Localization ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Positioning System ◽  
Indoor Environments ◽  
University Campus ◽  
Sources Of Information ◽  
Visual Place Recognition ◽  
Indoor Positioning System

WiFi-based fingerprinting is promising for practical indoor localization with smartphones because this technique provides absolute estimates of the current position, while the WiFi infrastructure is ubiquitous in the majority of indoor environments. However, the application of WiFi fingerprinting for positioning requires pre-surveyed signal maps and is getting more restricted in the recent generation of smartphones due to changes in security policies. Therefore, we sought new sources of information that can be fused into the existing indoor positioning framework, helping users to pinpoint their position, even with a relatively low-quality, sparse WiFi signal map. In this paper, we demonstrate that such information can be derived from the recognition of camera images. We present a way of transforming qualitative information of image similarity into quantitative constraints that are then fused into the graph-based optimization framework for positioning together with typical pedestrian dead reckoning (PDR) and WiFi fingerprinting constraints. Performance of the improved indoor positioning system is evaluated on different user trajectories logged inside an office building at our University campus. The results demonstrate that introducing additional sensing modality into the positioning system makes it possible to increase accuracy and simultaneously reduce the dependence on the quality of the pre-surveyed WiFi map and the WiFi measurements at run-time.

scholarly journals PEOPLE’S PPRESENCE EFFECT ON WLAN-BASED IPS’ ACCURACY

2015 ◽  
Vol 77 (9) ◽  
Author(s):  
Iyad H Alshami ◽  
Noor Azurati Ahmad ◽  
Shamsul Sahibuddin
Keyword(s):  
Low Cost ◽  
Signal Strength ◽  
Access Point ◽  
Received Signal Strength ◽  
Positioning System ◽  
Indoor Environments ◽  
Received Signal Strength Indicator ◽  
Indoor Positioning System ◽  
Closed Environment ◽  
Presence Of People

In order to enable Location Based Service (LBS) closed environment, many technologies have been investigated to replace the Global Positioning System (GPS) in the localization process in indoor environments. WLAN is considered as the most suitable and powerful technology for Indoor Positioning System (IPS) due to its widespread coverage and low cost. Although WLAN Received Signal Strength Indicator (RSS) fingerprinting can be considered as the most accurate IPS method, this accuracy can be weakened due to WLAN RSS fluctuation. WLAN RSS fluctuates due to the multipath being influenced by obstacles presence. People presence under WLAN coverage can be considered as one of the main obstacles which can affect the WLAN-IPS accuracy. This research presents experimental results demonstrating that people’s presence between access point (AP) and mobile device (MD) reduces the received signal strength by -2dBm to -5dBm. This reduction in RSS can lead to distance error greater than or equal to 2m. Hence, any accurate IPS must consider the presence of people in the indoor environment. 

scholarly journals Deep-Learning-Based Wi-Fi Indoor Positioning System Using Continuous CSI of Trajectories

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5776
Author(s):  
Zhongfeng Zhang ◽  
Minjae Lee ◽  
Seungwon Choi
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Software Radio ◽  
Multipath Fading ◽  
Indoor Positioning ◽  
Training Dataset ◽  
Positioning System ◽  
Indoor Environments ◽  
Generative Adversarial Network ◽  
Indoor Positioning System

In a Wi-Fi indoor positioning system (IPS), the performance of the IPS depends on the channel state information (CSI), which is often limited due to the multipath fading effect, especially in indoor environments involving multiple non-line-of-sight propagation paths. In this paper, we propose a novel IPS utilizing trajectory CSI observed from predetermined trajectories instead of the CSI collected at each stationary location; thus, the proposed method enables all the CSI along each route to be continuously encountered in the observation. Further, by using a generative adversarial network (GAN), which helps enlarge the training dataset, the cost of trajectory CSI collection can be significantly reduced. To fully exploit the trajectory CSI’s spatial and temporal information, the proposed IPS employs a deep learning network of a one-dimensional convolutional neural network–long short-term memory (1DCNN-LSTM). The proposed IPS was hardware-implemented, where digital signal processors and a universal software radio peripheral were used as a modem and radio frequency transceiver, respectively, for both access point and mobile device of Wi-Fi. We verified that the proposed IPS based on the trajectory CSI far outperforms the state-of-the-art IPS based on the CSI collected from stationary locations through extensive experimental tests and computer simulations.

scholarly journals Accurate indoor positioning system based on modify nearest point technique

2022 ◽  
Vol 12 (2) ◽  
pp. 1593
Author(s):  
Omar Ibrahim Mustafa ◽  
Hawraa Lateef Joey ◽  
Noor Abd AlSalam ◽  
Ibrahim Zeghaiton Chaloob
Keyword(s):  
Indoor Localization ◽  
Signal Strength ◽  
Real Data ◽  
Reference Points ◽  
Positioning System ◽  
Indoor Environments ◽  
Nearest Point ◽  
The Impact ◽  
Indoor Positioning System

Wireless fidelity (Wi-Fi) is common technology for indoor environments that use to estimate required distances, to be used for indoor localization. Due to multiple source of noise and interference with other signal, the receive signal strength (RSS) measurements unstable. The impression about targets environments should be available to estimate accurate targets location. The Wi-Fi fingerprint technique is widely implemented to build database matching with real data, but the challenges are the way of collect accurate data to be the reference and the impact of different environments on signals measurements. In this paper, optimum system proposed based on modify nearest point (MNP). To implement the proposal, 78 points measured to be the reference points recorded in each environment around the targets. Also, the case study building is separated to 7 areas, where the segmentation of environments leads to ability of dynamic parameters assignments. Moreover, database based on optimum data collected at each time using 63 samples in each point and the average will be final measurements. Then, the nearest point into specific environment has been determined by compared with at least four points. The results show that the errors of indoor localization were less than (0.102 m).

scholarly journals Scale up to infinity: the UWB Indoor Global Positioning System

2021 ◽  
Author(s):  
Luca Santoro ◽  
Davide Brunelli ◽  
daniele fontanelli ◽  
matteo nardello
Keyword(s):  
Scale Up ◽  
Active Role ◽  
Maximum Error ◽  
Absolute Maximum ◽  
Positioning System ◽  
Indoor Environments ◽  
Positioning Systems ◽  
Transmission Mechanisms ◽  
Local Positioning System ◽  
Update Rate

Determining assets position with high accuracy and scalability is one of the most investigated technology on the market. The accuracy provided by satellites-based positioning systems (i.e., GLONASS or Galileo) is not always sufficient when a decimeter-level accuracy is required or when there is the need of localising entities that operate inside indoor environments. Scalability is also a recurrent problem when dealing with indoor positioning systems. This paper presents an innovative UWB Indoor GPS-Like local positioning system able to tracks any number of assets without decreasing measurements update rate. To increase the system’s accuracy the mathematical model and the sources of uncertainties are investigated. Results highlight how the proposed implementation provides positioning information with an absolute maximum error below 20 cm. Scalability is also resolved thanks to DTDoA transmission mechanisms not requiring an active role from the asset to be tracked.

scholarly journals Multi-Sensor Accurate Forklift Location and Tracking Simulation in Industrial Indoor Environments

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1152 ◽  
Author(s):  
Valentín Barral ◽  
Pedro Suárez-Casal ◽  
Carlos J. Escudero ◽  
José A. García-Naya
Keyword(s):  
Inertial Sensor ◽  
Wireless Channel ◽  
Good Choice ◽  
Ultra Wideband ◽  
Positioning System ◽  
Indoor Environments ◽  
Location Algorithm ◽  
Industrial Environments ◽  
Indoor Scenarios ◽  
Industrial Problem

Location and tracking needs are becoming more prominent in industrial environments nowadays. Process optimization, traceability or safety are some of the topics where a positioning system can operate to improve and increase the productivity of a factory or warehouse. Among the different options, solutions based on ultra-wideband (UWB) have emerged during recent years as a good choice to obtain highly accurate estimations in indoor scenarios. However, the typical harsh wireless channel conditions found inside industrial environments, together with interferences caused by workers and machinery, constitute a challenge for this kind of system. This paper describes a real industrial problem (location and tracking of forklift trucks) that requires precise internal positioning and presents a study on the feasibility of meeting this challenge using UWB technology. To this end, a simulator of this technology was created based on UWB measurements from a set of real sensors. This simulator was used together with a location algorithm and a physical model of the forklift to obtain estimations of position in different scenarios with different obstacles. Together with the simulated UWB sensor, an additional inertial sensor and optical sensor were modeled in order to test its effect on supporting the location based on UWB. All the software created for this work is published under an open-source license and is publicly available.

scholarly journals Calibration of Beacons for Indoor Environments based on a Digital Map and Heuristic Information

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 670
Author(s):  
David Gualda ◽  
Jesús Ureña ◽  
José Alcalá ◽  
Carlos Santos
Keyword(s):  
Genetic Algorithm ◽  
Indoor Environment ◽  
Harmony Search ◽  
Positioning System ◽  
Indoor Environments ◽  
Angle Of Incidence ◽  
Distance Measurements ◽  
Digital Map ◽  
Local Positioning System ◽  
Numerical Minimization

This paper proposes an algorithm for calibrating the position of beacons which are placed on the ceiling of an indoor environment. In this context, the term calibration is used to estimate the position coordinates of a beacon related to a known reference system in a map. The positions of a set of beacons are used for indoor positioning purposes. The operation of the beacons can be based on different technologies such as radiofrequency (RF), infrared (IR) or ultrasound (US), among others. In this case we are interested in the positions of several beacons that compose an Ultrasonic Local Positioning System (ULPS) placed on different strategic points of the building. The calibration proposal uses several distances from a beacon to the neighbor walls measured by a laser meter. These measured distances, the map of the building in a vector format and other heuristic data (such as the region in which the beacon is located, the approximate orientation of the distance measurements to the walls and the equations in the map coordinate system of the line defining these walls) are the inputs of the proposed algorithm. The output is the best estimation of the position of the beacon. The process is repeated for all the beacons. To find the best estimation of the position of the beacons we have implemented a numerical minimization based on the use of a Genetic Algorithm (GA) and a Harmony Search (HS) methods. The proposal has been validated with simulations and real experiments, obtaining the positions of the beacons and an estimation of the error associated that depends on which walls (and the angle of incidence of the laser) are selected to make the distance measurements.

Sign in / Sign up

Export Citation Format

Share Document