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Real-time Locating Systems for indoor applications: the methodological customization approach
Blekinge Tekniska Högskola, Fakulteten för teknikvetenskaper, Institutionen för tillämpad signalbehandling. DAC SA.ORCID-id: 0000-0003-0910-8643
2019 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Emerging wireless technologies increase the potential and effectiveness of wireless Real-time Locating Systems (RTLSs), which precisely localize the position, and identify things and people in real time. Among many applications, RTLSs are widely used in the industrial sector for indoor logistics and safety applications. However, signal interferences, which affect the system’s performance, are a serious issue of all indoor RTLS applications. Among others, the interferences are caused by the changeable working environment, the geometry and structure of the space, furnishing, and other obstacles. A customization of the RTLS’s architecture and localization algorithm may provide a way to overcome the interference problem and then enhance the systems’ performance.

The objective of this thesis is to develop and implement customization methods, which enhance system performance in the changeable working environment without compromising the functional and non-functional requirements defined by future users and stakeholders. The customized solution is to be based on the comprehensive methodological analysis of the system’s technical and environmental constraints, along with the requirements specified by the application field. The customization process covers the selection, adjustment and adaptation of the wireless technologies and methods in order to enhance the location system’s performance, in terms of accuracy and precision without compromising its simplicity and price.

In this research, wireless technologies of Radio Frequency Identification (RFID) and Ultra-wideband (UWB) are applied. The related indoor localization methods, such as, ranging techniques based on Received Signal Strength (RSS) and Angle of Arrival (AoA), are a thesis focus. Moreover, estimation methods like Fingerprinting and Angulation are used.

One of the proposed customization methods of RFID-based 3D RTLS, refers to the heuristic analysis-based optimization of a number and configuration of readers. For the same type of system, an alternative way of performance improvement is a customization of localization algorithm, explicitly the Neural Network-based estimation algorithm and its structural features and training methods.

Also in this thesis, performance improvement methods of the AoA-based RTLS operating in an UWB technology are proposed. The proposed customization of this system type is based on the uncertainty pattern defined by a statistical uncertainty model, which maps the localization uncertainty in terms of precision in the 2D workspace. The model depicts how the localization uncertainty depends on an arrangement of Location Sensors and workspace geometry. Another proposed customization method is realized by defining and implementing correction vectors for different working environments, which enhance the system’s performance in terms of its accuracy.

This thesis consists of two parts. Part I, Prolegomena, presents the overview of applied theories and research methods. This part aims to illustrate the links between the articles constituting the second part of the dissertation. Part II, Papers consists of five reformatted papers already published in peer reviewed journals and conferences.

sted, utgiver, år, opplag, sider
Karlskrona: Blekinge Tekniska Högskola, 2019. , s. 204
Serie
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 08
Emneord [en]
Accuracy and Precision, Angle of Arrival, Fingerprinting Method, Indoor Localization, Indoor Positioning System, Multi-Sensor System, Neural Network, Radio Frequency Identification - RFID, Real Time Locating System, Received Signal Strength, RFID Network Planning, Scene Analysis, Sensors Arrangement, System Customization, Uncertainty, Uncertainty Map, User Driven Design
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-17740ISBN: 978-91-7295-373-4 (tryckt)OAI: oai:DiVA.org:bth-17740DiVA, id: diva2:1298734
Disputas
2019-05-03, J1650, Blekinge Tekniska Högskola, Campus Gräsvik, Karlskrona, 13:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2019-03-28 Laget: 2019-03-25 Sist oppdatert: 2019-06-18bibliografisk kontrollert
Delarbeid
1. Performance analysis of an RFID-based 3D indoor positioning system combining scene analysis and neural network methods
Åpne denne publikasjonen i ny fane eller vindu >>Performance analysis of an RFID-based 3D indoor positioning system combining scene analysis and neural network methods
2013 (engelsk)Inngår i: Scientific Papers of Faculty of Electrical and Control Engineering Gdansk University of Technology, ISSN 1425-5766, nr 34, s. 29-33Artikkel, forskningsoversikt (Fagfellevurdert) Published
Abstract [en]

The main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and physical experiments validate that the proposed positioning system improves the localization accuracy of an RFID tag compared with well-known Scene Analysis technique solutions

sted, utgiver, år, opplag, sider
Faculty of Electrical and Control Engineering Gdansk University of Technology, 2013
Emneord
indoor positioning system, neural network, radio frequency identification, scene analysis
HSV kategori
Identifikatorer
urn:nbn:se:bth-6613 (URN)oai:bth.se:forskinfo7D45085B55291527C1257D5D0046F0BC (Lokal ID)oai:bth.se:forskinfo7D45085B55291527C1257D5D0046F0BC (Arkivnummer)oai:bth.se:forskinfo7D45085B55291527C1257D5D0046F0BC (OAI)
Tilgjengelig fra: 2014-10-03 Laget: 2014-09-24 Sist oppdatert: 2019-03-28bibliografisk kontrollert
2. RFID: Hybrid Scene Analysis-Neural Network System for 3D Indoor Positioning optimal system arrangement approach
Åpne denne publikasjonen i ny fane eller vindu >>RFID: Hybrid Scene Analysis-Neural Network System for 3D Indoor Positioning optimal system arrangement approach
2014 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The purpose of this research is to find an optimal number and configuration of readers in RFID based 3D Indoor Positioning System. The system applies a Hybrid Scene Analysis - Neural Network algorithm to estimate target's position with a desired accuracy. The system's accuracy and cost depend on a number of utilized readers and their arrangement. Readers' deployment is crucial for the localization accuracy too. The system optimization enhances the system cost-efficiency. The arrangement analysis was based on simulations and validated by physical experiment. The results of this research define a trade-off between a number of readers and their deployment and the system performance in terms of localization accuracy.

sted, utgiver, år, opplag, sider
Montevideo: IEEE, 2014
Emneord
3D indoor positioning, neural network system, optimal system arrangement, RFID network planning, optimization, radiofrequency identification, reader configuration, scene analysis
HSV kategori
Identifikatorer
urn:nbn:se:bth-6615 (URN)10.1109/I2MTC.2014.6860732 (DOI)oai:bth.se:forskinfoB29987C9B8234376C1257D550029E77A (Lokal ID)oai:bth.se:forskinfoB29987C9B8234376C1257D550029E77A (Arkivnummer)oai:bth.se:forskinfoB29987C9B8234376C1257D550029E77A (OAI)
Konferanse
Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014 IEEE International
Tilgjengelig fra: 2014-09-30 Laget: 2014-09-16 Sist oppdatert: 2019-03-28bibliografisk kontrollert
3. Performance improvement of NN based RTLS by customization of NN structure: Heuristic approach
Åpne denne publikasjonen i ny fane eller vindu >>Performance improvement of NN based RTLS by customization of NN structure: Heuristic approach
2015 (engelsk)Inngår i: Proceedings of the International Conference on Sensing Technology, ICST, IEEE Computer Society, 2015, s. 278-283Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The purpose of this research is to improve performance of the Hybrid Scene Analysis - Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis is suitable to evaluate NN performance for different environmental conditions. Efficiency of the proposed customization of a Neural Network is verified by simulations and validated by physical experiments. This research also concerns the influence of size of Neural Network training set. The results prove that, better localization accuracy is with a NN system which is properly customized with respect to a training method, number of neurons and type of transfer function in the hidden layer and also type of transfer function in the output layer.

sted, utgiver, år, opplag, sider
IEEE Computer Society, 2015
Serie
Proceedings of the International Conference on Sensing Technology, ICST, ISSN 2156-8065
Emneord
Algorithms; Complex networks; Heuristic methods; Network architecture; Neural networks; Optimization; Radio frequency identification (RFID); RSS; Transfer functions, Accuracy and precision; Environmental conditions; Indoor localization; Localization accuracy; Neural network training; Operating environment; Real-Time Locating Systems; Scene analysis, Indoor positioning systems
HSV kategori
Identifikatorer
urn:nbn:se:bth-13146 (URN)10.1109/ICSensT.2015.7438407 (DOI)000380410400054 ()2-s2.0-84964882100 (Scopus ID)9781479963140 (ISBN)
Konferanse
9th International Conference on Sensing Technology, ICST 2015; Auckland; New Zealand
Merknad

Conference of 9th International Conference on Sensing Technology, ICST 2015 ; Conference Date: 8 December 2015 Through 11 December 2015; Conference Code:121054

Tilgjengelig fra: 2016-10-04 Laget: 2016-10-03 Sist oppdatert: 2019-03-28bibliografisk kontrollert
4. Using the fingerprinting method to customize RTLS based on the AoA ranging technique
Åpne denne publikasjonen i ny fane eller vindu >>Using the fingerprinting method to customize RTLS based on the AoA ranging technique
2016 (engelsk)Inngår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 16, nr 6, artikkel-id 876Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Real-time Locating Systems (RTLSs) have the ability to precisely locate the position of things and people in real time. They are needed for security and emergency applications, but also for healthcare and home care appliances. The research aims for developing an analytical method to customize RTLSs, in order to improve localization performance in terms of precision. The proposed method is based on Angle of Arrival (AoA), a ranging technique and fingerprinting method along with an analytically defined uncertainty of AoA, and a localization uncertainty map. The presented solution includes three main concerns: geometry of indoor space, RTLS arrangement, and a statistical approach to localization precision of a pair of location sensors using an AoA signal. An evaluation of the implementation of the customized RTLS validates the analytical model of the fingerprinting map. The results of simulations and physical experiments verify the proposed method. The research confirms that the analytically established fingerprint map is the valid representation of RTLS’ performance in terms of precision. Furthermore, the research demonstrates an impact of workspace geometry and workspace layout onto the RTLS’ performance. Moreover, the studies show how the size and shape of a workspace and the placement of the calibration point affect the fingerprint map. Withal, the performance investigation defines the most effective arrangement of location sensors and its influence on localization precision. © 2016 by the authors; licensee MDPI, Basel, Switzerland.

sted, utgiver, år, opplag, sider
MDPI AG, 2016
Emneord
Calibration; Direction of arrival; Location, Accuracy and precision; Angle of arrival; Calibration points; Fingerprinting methods; Indoor localization systems; Real-Time Locating Systems, Real time systems
HSV kategori
Identifikatorer
urn:nbn:se:bth-12778 (URN)10.3390/s16060876 (DOI)000378756500124 ()2-s2.0-84974803245 (Scopus ID)
Tilgjengelig fra: 2016-06-30 Laget: 2016-06-30 Sist oppdatert: 2019-03-28bibliografisk kontrollert
5. Customization of UWB 3D-RTLS based on the new uncertainty model of the AoA ranging technique
Åpne denne publikasjonen i ny fane eller vindu >>Customization of UWB 3D-RTLS based on the new uncertainty model of the AoA ranging technique
2017 (engelsk)Inngår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, nr 2, artikkel-id 227Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The increased potential and effectiveness of Real-time Locating Systems (RTLSs) substantially influence their application spectrum. They are widely used, inter alia, in the industrial sector, healthcare, home care, and in logistic and security applications. The research aims to develop an analytical method to customize UWB-based RTLS, in order to improve their localization performance in terms of accuracy and precision. The analytical uncertainty model of Angle of Arrival (AoA) localization in a 3D indoor space, which is the foundation of the customization concept, is established in a working environment. Additionally, a suitable angular-based 3D localization algorithm is introduced. The paper investigates the following issues: the influence of the proposed correction vector on the localization accuracy; the impact of the system’s configuration and LS’s relative deployment on the localization precision distribution map. The advantages of the method are verified by comparing them with a reference commercial RTLS localization engine. The results of simulations and physical experiments prove the value of the proposed customization method. The research confirms that the analytical uncertainty model is the valid representation of RTLS’ localization uncertainty in terms of accuracy and precision and can be useful for its performance improvement. The research shows, that the Angle of Arrival localization in a 3D indoor space applying the simple angular-based localization algorithm and correction vector improves of localization accuracy and precision in a way that the system challenges the reference hardware advanced localization engine. Moreover, the research guides the deployment of location sensors to enhance the localization precision.

sted, utgiver, år, opplag, sider
MDPI, AG, 2017
Emneord
Accuracy and precision, Angle of arrival, Correction vector, Indoor localization systems, Real-time locating systems, Direction of arrival, Engines, Location, Real time systems, Vector spaces, Analytical uncertainty, Localization accuracy, Localization algorithm, Localization performance, Indoor positioning systems
HSV kategori
Identifikatorer
urn:nbn:se:bth-13927 (URN)10.3390/s17020227 (DOI)000395482700011 ()2-s2.0-85011076149 (Scopus ID)
Merknad

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Tilgjengelig fra: 2017-02-22 Laget: 2017-02-22 Sist oppdatert: 2019-03-28bibliografisk kontrollert

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