Particle Filtering with Geospatial Analysis for Indoor Positioning

Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Harder, Dorian [verfasserIn] Sternberg, Harald - 1963- [akademischer betreuerIn] Shoushtari, Hossein [akademischer betreuerIn]
Körperschaften:	HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik [Grad-verleihende Institution]
Hochschulschrift:	Masterarbeit ; HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik ; 2021

Format:	E-Book
Sprache:	Englisch

Erschienen:	Hamburg: HafenCity Universität Hamburg ; 2021

Rechteinformationen:	Open Access Namensnennung 3.0 International ; CC BY 3.0

Schlagwörter:	Particle filter indoor positioning smartphone Partikelfilter Geodatenanalyse Indoor-Positionierung
Formangabe:	Hochschulschrift

Systematik:	ZI 9070

Umfang:	1 Online-Ressource

Links:	Link aufrufen Link aufrufen Link aufrufen Link aufrufen

DOI / URN:	urn:nbn:de:gbv:1373-repos-7426

Katalog-ID:	1776437985

Internformat


LEADER	01000cam a2200265 4500
001	1776437985
003	DE-627
005	20230810132526.0
007	cr uuu---uuuuu
008	211109s2021 gw \|\|\|\|\|om 00\| \|\|eng c
024	7		\|a urn:nbn:de:gbv:1373-repos-7426 \|2 urn
035			\|a (DE-627)1776437985
035			\|a (DE-599)KXP1776437985
040			\|a DE-627 \|b ger \|c DE-627 \|e rda
041			\|a eng
044			\|c XA-DE-HH
082	0		\|a 621.384191 \|q DE-101
082	0		\|a 004
082	0	4	\|a 621.3 \|q DE-101
084			\|a ZI 9070 \|2 rvk \|0 (DE-625)rvk/156699:
100	1		\|a Harder, Dorian \|e verfasserin \|4 aut
245	1	0	\|a Particle Filtering with Geospatial Analysis for Indoor Positioning \|c Dorian Harder
247	1	0	\|a Partikel-Filter mit Geodaten-Analyse für die Indoor Positionierung \|f Übers. des Hauptsacht.
264		1	\|a Hamburg \|b HafenCity Universität Hamburg \|c 2021
300			\|a 1 Online-Ressource
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
502			\|b Masterarbeit \|c HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik \|d 2021
506	0		\|q DE-1373 \|a Open Access \|e Controlled Vocabulary for Access Rights \|u http://purl.org/coar/access_right/c_abf2
520			\|a Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods.
540			\|q DE-1373 \|a Namensnennung 3.0 International \|f CC BY 3.0 \|2 cc \|u https://creativecommons.org/licenses/by/3.0/
650		7	\|a Particle filter \|2 DSpace
650		7	\|a indoor positioning \|2 DSpace
650		7	\|a smartphone \|2 DSpace
650		7	\|a Partikelfilter \|2 DSpace
650		7	\|a Geodatenanalyse \|2 DSpace
650		7	\|a Indoor-Positionierung \|2 DSpace
655		7	\|a Hochschulschrift \|0 (DE-588)4113937-9 \|0 (DE-627)105825778 \|0 (DE-576)209480580 \|2 gnd-content
700	1		\|a Sternberg, Harald \|d 1963- \|e akademischer betreuerin \|0 (DE-588)122059360 \|0 (DE-627)70575572X \|0 (DE-576)29307089X \|4 dgs
700	1		\|a Shoushtari, Hossein \|e akademischer betreuerin \|4 dgs
710	2		\|a HafenCity Universität Hamburg \|b Institut für Geodäsie und Geoinformatik \|e Grad-verleihende Institution \|4 dgg
856	4	0	\|u https://repos.hcu-hamburg.de/handle/hcu/590 \|v 2021-11-17 \|x Resolving-System \|z kostenfrei
856	4	0	\|u https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426 \|v 2021-11-17 \|x Resolving-System
856	4	0	\|u https://d-nb.info/1243507659/34 \|v 2021-11-17 \|x Langzeitarchivierung Nationalbibliothek
912			\|a GBV-ODiss
912			\|a GBV_ILN_370
912			\|a ISIL_DE-1373
912			\|a SYSFLAG_1
912			\|a GBV_KXP
912			\|a GBV_ILN_2403
912			\|a ISIL_DE-LFER
935			\|i DSpace
936	r	v	\|a ZI 9070 \|b Geodätisches Messen, Messverfahren \|k Technik \|k Bauingenieurwesen \|k Geodäsie, Vermessung \|k Geodätisches Messen, Messverfahren \|0 (DE-627)1271600641 \|0 (DE-625)rvk/156699: \|0 (DE-576)201600641
951			\|a BO
953			\|2 045F \|a 621.384191
953			\|2 045F \|a 004
980			\|2 370 \|1 01 \|x 4370 \|b 3999998768 \|h olr-stud \|y z \|z 09-11-21
980			\|2 2403 \|1 01 \|x DE-LFER \|b 4014652718 \|c 00 \|f --%%-- \|d --%%-- \|e n \|j --%%-- \|y l01 \|z 06-12-21
981			\|2 370 \|1 01 \|x 4370 \|r https://repos.hcu-hamburg.de/handle/hcu/590
981			\|2 2403 \|1 01 \|x DE-LFER \|r https://repos.hcu-hamburg.de/handle/hcu/590
995			\|2 370 \|1 01 \|x 4370 \|a olr-stud
995			\|2 370 \|1 01 \|x 4370 \|a olr-free
998			\|2 370 \|1 01 \|x 4370 \|0 2021.11.09

Indexfelder

author_variant	d h dh
matchkey_str	harderdoriansternbergharaldshoushtarihos:2021----:atceitrnwtgoptaaayifr
hierarchy_sort_str	2021
publishDate	2021
allfields	urn:nbn:de:gbv:1373-repos-7426 urn (DE-627)1776437985 (DE-599)KXP1776437985 DE-627 ger DE-627 rda eng XA-DE-HH 621.384191 DE-101 004 621.3 DE-101 ZI 9070 rvk (DE-625)rvk/156699: Harder, Dorian verfasserin aut Particle Filtering with Geospatial Analysis for Indoor Positioning Dorian Harder Partikel-Filter mit Geodaten-Analyse für die Indoor Positionierung Übers. des Hauptsacht. Hamburg HafenCity Universität Hamburg 2021 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Masterarbeit HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik 2021 DE-1373 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods. DE-1373 Namensnennung 3.0 International CC BY 3.0 cc https://creativecommons.org/licenses/by/3.0/ Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung DSpace Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Sternberg, Harald 1963- akademischer betreuerin (DE-588)122059360 (DE-627)70575572X (DE-576)29307089X dgs Shoushtari, Hossein akademischer betreuerin dgs HafenCity Universität Hamburg Institut für Geodäsie und Geoinformatik Grad-verleihende Institution dgg https://repos.hcu-hamburg.de/handle/hcu/590 2021-11-17 Resolving-System kostenfrei https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426 2021-11-17 Resolving-System https://d-nb.info/1243507659/34 2021-11-17 Langzeitarchivierung Nationalbibliothek GBV-ODiss GBV_ILN_370 ISIL_DE-1373 SYSFLAG_1 GBV_KXP GBV_ILN_2403 ISIL_DE-LFER DSpace ZI 9070 Geodätisches Messen, Messverfahren Technik Bauingenieurwesen Geodäsie, Vermessung Geodätisches Messen, Messverfahren (DE-627)1271600641 (DE-625)rvk/156699: (DE-576)201600641 BO 045F 621.384191 045F 004 370 01 4370 3999998768 olr-stud z 09-11-21 2403 01 DE-LFER 4014652718 00 --%%-- --%%-- n --%%-- l01 06-12-21 370 01 4370 https://repos.hcu-hamburg.de/handle/hcu/590 2403 01 DE-LFER https://repos.hcu-hamburg.de/handle/hcu/590 370 01 4370 olr-stud 370 01 4370 olr-free 370 01 4370 2021.11.09
spelling	urn:nbn:de:gbv:1373-repos-7426 urn (DE-627)1776437985 (DE-599)KXP1776437985 DE-627 ger DE-627 rda eng XA-DE-HH 621.384191 DE-101 004 621.3 DE-101 ZI 9070 rvk (DE-625)rvk/156699: Harder, Dorian verfasserin aut Particle Filtering with Geospatial Analysis for Indoor Positioning Dorian Harder Partikel-Filter mit Geodaten-Analyse für die Indoor Positionierung Übers. des Hauptsacht. Hamburg HafenCity Universität Hamburg 2021 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Masterarbeit HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik 2021 DE-1373 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods. DE-1373 Namensnennung 3.0 International CC BY 3.0 cc https://creativecommons.org/licenses/by/3.0/ Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung DSpace Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Sternberg, Harald 1963- akademischer betreuerin (DE-588)122059360 (DE-627)70575572X (DE-576)29307089X dgs Shoushtari, Hossein akademischer betreuerin dgs HafenCity Universität Hamburg Institut für Geodäsie und Geoinformatik Grad-verleihende Institution dgg https://repos.hcu-hamburg.de/handle/hcu/590 2021-11-17 Resolving-System kostenfrei https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426 2021-11-17 Resolving-System https://d-nb.info/1243507659/34 2021-11-17 Langzeitarchivierung Nationalbibliothek GBV-ODiss GBV_ILN_370 ISIL_DE-1373 SYSFLAG_1 GBV_KXP GBV_ILN_2403 ISIL_DE-LFER DSpace ZI 9070 Geodätisches Messen, Messverfahren Technik Bauingenieurwesen Geodäsie, Vermessung Geodätisches Messen, Messverfahren (DE-627)1271600641 (DE-625)rvk/156699: (DE-576)201600641 BO 045F 621.384191 045F 004 370 01 4370 3999998768 olr-stud z 09-11-21 2403 01 DE-LFER 4014652718 00 --%%-- --%%-- n --%%-- l01 06-12-21 370 01 4370 https://repos.hcu-hamburg.de/handle/hcu/590 2403 01 DE-LFER https://repos.hcu-hamburg.de/handle/hcu/590 370 01 4370 olr-stud 370 01 4370 olr-free 370 01 4370 2021.11.09
allfields_unstemmed	urn:nbn:de:gbv:1373-repos-7426 urn (DE-627)1776437985 (DE-599)KXP1776437985 DE-627 ger DE-627 rda eng XA-DE-HH 621.384191 DE-101 004 621.3 DE-101 ZI 9070 rvk (DE-625)rvk/156699: Harder, Dorian verfasserin aut Particle Filtering with Geospatial Analysis for Indoor Positioning Dorian Harder Partikel-Filter mit Geodaten-Analyse für die Indoor Positionierung Übers. des Hauptsacht. Hamburg HafenCity Universität Hamburg 2021 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Masterarbeit HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik 2021 DE-1373 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods. DE-1373 Namensnennung 3.0 International CC BY 3.0 cc https://creativecommons.org/licenses/by/3.0/ Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung DSpace Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Sternberg, Harald 1963- akademischer betreuerin (DE-588)122059360 (DE-627)70575572X (DE-576)29307089X dgs Shoushtari, Hossein akademischer betreuerin dgs HafenCity Universität Hamburg Institut für Geodäsie und Geoinformatik Grad-verleihende Institution dgg https://repos.hcu-hamburg.de/handle/hcu/590 2021-11-17 Resolving-System kostenfrei https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426 2021-11-17 Resolving-System https://d-nb.info/1243507659/34 2021-11-17 Langzeitarchivierung Nationalbibliothek GBV-ODiss GBV_ILN_370 ISIL_DE-1373 SYSFLAG_1 GBV_KXP GBV_ILN_2403 ISIL_DE-LFER DSpace ZI 9070 Geodätisches Messen, Messverfahren Technik Bauingenieurwesen Geodäsie, Vermessung Geodätisches Messen, Messverfahren (DE-627)1271600641 (DE-625)rvk/156699: (DE-576)201600641 BO 045F 621.384191 045F 004 370 01 4370 3999998768 olr-stud z 09-11-21 2403 01 DE-LFER 4014652718 00 --%%-- --%%-- n --%%-- l01 06-12-21 370 01 4370 https://repos.hcu-hamburg.de/handle/hcu/590 2403 01 DE-LFER https://repos.hcu-hamburg.de/handle/hcu/590 370 01 4370 olr-stud 370 01 4370 olr-free 370 01 4370 2021.11.09
allfieldsGer	urn:nbn:de:gbv:1373-repos-7426 urn (DE-627)1776437985 (DE-599)KXP1776437985 DE-627 ger DE-627 rda eng XA-DE-HH 621.384191 DE-101 004 621.3 DE-101 ZI 9070 rvk (DE-625)rvk/156699: Harder, Dorian verfasserin aut Particle Filtering with Geospatial Analysis for Indoor Positioning Dorian Harder Partikel-Filter mit Geodaten-Analyse für die Indoor Positionierung Übers. des Hauptsacht. Hamburg HafenCity Universität Hamburg 2021 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Masterarbeit HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik 2021 DE-1373 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods. DE-1373 Namensnennung 3.0 International CC BY 3.0 cc https://creativecommons.org/licenses/by/3.0/ Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung DSpace Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Sternberg, Harald 1963- akademischer betreuerin (DE-588)122059360 (DE-627)70575572X (DE-576)29307089X dgs Shoushtari, Hossein akademischer betreuerin dgs HafenCity Universität Hamburg Institut für Geodäsie und Geoinformatik Grad-verleihende Institution dgg https://repos.hcu-hamburg.de/handle/hcu/590 2021-11-17 Resolving-System kostenfrei https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426 2021-11-17 Resolving-System https://d-nb.info/1243507659/34 2021-11-17 Langzeitarchivierung Nationalbibliothek GBV-ODiss GBV_ILN_370 ISIL_DE-1373 SYSFLAG_1 GBV_KXP GBV_ILN_2403 ISIL_DE-LFER DSpace ZI 9070 Geodätisches Messen, Messverfahren Technik Bauingenieurwesen Geodäsie, Vermessung Geodätisches Messen, Messverfahren (DE-627)1271600641 (DE-625)rvk/156699: (DE-576)201600641 BO 045F 621.384191 045F 004 370 01 4370 3999998768 olr-stud z 09-11-21 2403 01 DE-LFER 4014652718 00 --%%-- --%%-- n --%%-- l01 06-12-21 370 01 4370 https://repos.hcu-hamburg.de/handle/hcu/590 2403 01 DE-LFER https://repos.hcu-hamburg.de/handle/hcu/590 370 01 4370 olr-stud 370 01 4370 olr-free 370 01 4370 2021.11.09
allfieldsSound	urn:nbn:de:gbv:1373-repos-7426 urn (DE-627)1776437985 (DE-599)KXP1776437985 DE-627 ger DE-627 rda eng XA-DE-HH 621.384191 DE-101 004 621.3 DE-101 ZI 9070 rvk (DE-625)rvk/156699: Harder, Dorian verfasserin aut Particle Filtering with Geospatial Analysis for Indoor Positioning Dorian Harder Partikel-Filter mit Geodaten-Analyse für die Indoor Positionierung Übers. des Hauptsacht. Hamburg HafenCity Universität Hamburg 2021 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Masterarbeit HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik 2021 DE-1373 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods. DE-1373 Namensnennung 3.0 International CC BY 3.0 cc https://creativecommons.org/licenses/by/3.0/ Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung DSpace Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Sternberg, Harald 1963- akademischer betreuerin (DE-588)122059360 (DE-627)70575572X (DE-576)29307089X dgs Shoushtari, Hossein akademischer betreuerin dgs HafenCity Universität Hamburg Institut für Geodäsie und Geoinformatik Grad-verleihende Institution dgg https://repos.hcu-hamburg.de/handle/hcu/590 2021-11-17 Resolving-System kostenfrei https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426 2021-11-17 Resolving-System https://d-nb.info/1243507659/34 2021-11-17 Langzeitarchivierung Nationalbibliothek GBV-ODiss GBV_ILN_370 ISIL_DE-1373 SYSFLAG_1 GBV_KXP GBV_ILN_2403 ISIL_DE-LFER DSpace ZI 9070 Geodätisches Messen, Messverfahren Technik Bauingenieurwesen Geodäsie, Vermessung Geodätisches Messen, Messverfahren (DE-627)1271600641 (DE-625)rvk/156699: (DE-576)201600641 BO 045F 621.384191 045F 004 370 01 4370 3999998768 olr-stud z 09-11-21 2403 01 DE-LFER 4014652718 00 --%%-- --%%-- n --%%-- l01 06-12-21 370 01 4370 https://repos.hcu-hamburg.de/handle/hcu/590 2403 01 DE-LFER https://repos.hcu-hamburg.de/handle/hcu/590 370 01 4370 olr-stud 370 01 4370 olr-free 370 01 4370 2021.11.09
language	English
format_phy_str_mv	Book
building	370 2403:0
institution	findex.gbv.de
selectbib_iln_str_mv	370@ 2403@01
topic_facet	Particle filter indoor positioning smartphone Partikelfilter Geodatenanalyse Indoor-Positionierung
hochschulschrift_txt_mv	Masterarbeit HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik 2021
dewey-raw	621.384191
isfreeaccess_bool	true
authorswithroles_txt_mv	Harder, Dorian @@aut@@ Sternberg, Harald @@dgs@@ Shoushtari, Hossein @@dgs@@
publishDateDaySort_date	2021-01-01T00:00:00Z
dewey-sort	3621.384191
id	1776437985
genre_facet	Hochschulschrift
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000cam a2200265 4500</leader><controlfield tag="001">1776437985</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230810132526.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">211109s2021 gw \|\|\|\|\|om 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">urn:nbn:de:gbv:1373-repos-7426</subfield><subfield code="2">urn</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)1776437985</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KXP1776437985</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="c">XA-DE-HH</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">621.384191</subfield><subfield code="q">DE-101</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">004</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">621.3</subfield><subfield code="q">DE-101</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ZI 9070</subfield><subfield code="2">rvk</subfield><subfield code="0">(DE-625)rvk/156699:</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Harder, Dorian</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Particle Filtering with Geospatial Analysis for Indoor Positioning</subfield><subfield code="c">Dorian Harder</subfield></datafield><datafield tag="247" ind1="1" ind2="0"><subfield code="a">Partikel-Filter mit Geodaten-Analyse für die Indoor Positionierung</subfield><subfield code="f">Übers. des Hauptsacht.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hamburg</subfield><subfield code="b">HafenCity Universität Hamburg</subfield><subfield code="c">2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="b">Masterarbeit</subfield><subfield code="c">HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik</subfield><subfield code="d">2021</subfield></datafield><datafield tag="506" ind1="0" ind2=" "><subfield code="q">DE-1373</subfield><subfield code="a">Open Access</subfield><subfield code="e">Controlled Vocabulary for Access Rights</subfield><subfield code="u">http://purl.org/coar/access_right/c_abf2</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="q">DE-1373</subfield><subfield code="a">Namensnennung 3.0 International</subfield><subfield code="f">CC BY 3.0</subfield><subfield code="2">cc</subfield><subfield code="u">https://creativecommons.org/licenses/by/3.0/</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Particle filter</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">indoor positioning</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">smartphone</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Partikelfilter</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Geodatenanalyse</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Indoor-Positionierung</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="a">Hochschulschrift</subfield><subfield code="0">(DE-588)4113937-9</subfield><subfield code="0">(DE-627)105825778</subfield><subfield code="0">(DE-576)209480580</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sternberg, Harald</subfield><subfield code="d">1963-</subfield><subfield code="e">akademischer betreuerin</subfield><subfield code="0">(DE-588)122059360</subfield><subfield code="0">(DE-627)70575572X</subfield><subfield code="0">(DE-576)29307089X</subfield><subfield code="4">dgs</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shoushtari, Hossein</subfield><subfield code="e">akademischer betreuerin</subfield><subfield code="4">dgs</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">HafenCity Universität Hamburg</subfield><subfield code="b">Institut für Geodäsie und Geoinformatik</subfield><subfield code="e">Grad-verleihende Institution</subfield><subfield code="4">dgg</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://repos.hcu-hamburg.de/handle/hcu/590</subfield><subfield code="v">2021-11-17</subfield><subfield code="x">Resolving-System</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426</subfield><subfield code="v">2021-11-17</subfield><subfield code="x">Resolving-System</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://d-nb.info/1243507659/34</subfield><subfield code="v">2021-11-17</subfield><subfield code="x">Langzeitarchivierung Nationalbibliothek</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV-ODiss</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ISIL_DE-1373</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_1</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_KXP</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2403</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ISIL_DE-LFER</subfield></datafield><datafield tag="935" ind1=" " ind2=" "><subfield code="i">DSpace</subfield></datafield><datafield tag="936" ind1="r" ind2="v"><subfield code="a">ZI 9070</subfield><subfield code="b">Geodätisches Messen, Messverfahren</subfield><subfield code="k">Technik</subfield><subfield code="k">Bauingenieurwesen</subfield><subfield code="k">Geodäsie, Vermessung</subfield><subfield code="k">Geodätisches Messen, Messverfahren</subfield><subfield code="0">(DE-627)1271600641</subfield><subfield code="0">(DE-625)rvk/156699:</subfield><subfield code="0">(DE-576)201600641</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">621.384191</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">004</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="b">3999998768</subfield><subfield code="h">olr-stud</subfield><subfield code="y">z</subfield><subfield code="z">09-11-21</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">2403</subfield><subfield code="1">01</subfield><subfield code="x">DE-LFER</subfield><subfield code="b">4014652718</subfield><subfield code="c">00</subfield><subfield code="f">--%%--</subfield><subfield code="d">--%%--</subfield><subfield code="e">n</subfield><subfield code="j">--%%--</subfield><subfield code="y">l01</subfield><subfield code="z">06-12-21</subfield></datafield><datafield tag="981" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="r">https://repos.hcu-hamburg.de/handle/hcu/590</subfield></datafield><datafield tag="981" ind1=" " ind2=" "><subfield code="2">2403</subfield><subfield code="1">01</subfield><subfield code="x">DE-LFER</subfield><subfield code="r">https://repos.hcu-hamburg.de/handle/hcu/590</subfield></datafield><datafield tag="995" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="a">olr-stud</subfield></datafield><datafield tag="995" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="a">olr-free</subfield></datafield><datafield tag="998" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="0">2021.11.09</subfield></datafield></record></collection>
standort_str_mv	--%%--
standort_iln_str_mv	2403:--%%-- DE-LFER:--%%--
author	Harder, Dorian
spellingShingle	Harder, Dorian ddc 621.384191 ddc 004 ddc 621.3 rvk ZI 9070 DSpace Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung Particle Filtering with Geospatial Analysis for Indoor Positioning
authorStr	Harder, Dorian
format	eBook
dewey-ones	621 - Applied physics 004 - Data processing & computer science
delete_txt_mv	keep
author_role	aut
typewithnormlink_str_mv	SubjectHeadingSensoStricto@(DE-588)4113937-9 SubjectHeading@(DE-588)4113937-9 DifferentiatedPerson@(DE-588)122059360 Person@(DE-588)122059360
collection	KXP GVK SWB
publishPlace	Hamburg
remote_str	true
abrufzeichen_iln_str_mv	370@olr-stud 370@olr-free
abrufzeichen_iln_scis_mv	370@olr-stud 370@olr-free
last_changed_iln_str_mv	370@09-11-21 2403@06-12-21
illustrated	Not Illustrated
topic_title	621.384191 DE-101 004 621.3 DE-101 ZI 9070 rvk (DE-625)rvk/156699 Particle Filtering with Geospatial Analysis for Indoor Positioning Dorian Harder Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung DSpace
publisher	HafenCity Universität Hamburg
publisherStr	HafenCity Universität Hamburg
topic	ddc 621.384191 ddc 004 ddc 621.3 rvk ZI 9070 DSpace Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung
topic_unstemmed	ddc 621.384191 ddc 004 ddc 621.3 rvk ZI 9070 DSpace Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung
topic_browse	ddc 621.384191 ddc 004 ddc 621.3 rvk ZI 9070 DSpace Particle filter DSpace indoor positioning DSpace smartphone DSpace Partikelfilter DSpace Geodatenanalyse DSpace Indoor-Positionierung
format_facet	Elektronische Bücher Bücher Elektronische Ressource Hochschulschriften
standort_txtP_mv	--%%--
format_main_str_mv	Text Buch
format_details_str_mv	Hochschulschrift
carriertype_str_mv	cr
author2_variant	h s hs h s hs
normlinkwithtype_str_mv	(DE-588)4113937-9@SubjectHeadingSensoStricto (DE-588)4113937-9@SubjectHeading (DE-588)122059360@DifferentiatedPerson (DE-588)122059360@Person
signature	--%%--
signature_str_mv	--%%--
dewey-tens	620 - Engineering 000 - Computer science, knowledge & systems
isfreeaccess_txt	true
normlinkwithrole_str_mv	(DE-588)4113937-9@@655@@ (DE-588)122059360@@dgs@@
title	Particle Filtering with Geospatial Analysis for Indoor Positioning
ctrlnum	(DE-627)1776437985 (DE-599)KXP1776437985
title_full	Particle Filtering with Geospatial Analysis for Indoor Positioning Dorian Harder
author_sort	Harder, Dorian
callnumber-first-code	-
lang_code	eng
selektneu_str_mv	370@2021.11.09
isOA_bool	true
dewey-hundreds	600 - Technology 000 - Computer science, information & general works
recordtype	marc
genre	Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content
publishDateSort	2021
contenttype_str_mv	txt
author_browse	Harder, Dorian
selectkey	370:z 2403:l
physical	1 Online-Ressource
class	621.384191 DE-101 004 621.3 DE-101 ZI 9070 rvk (DE-625)rvk/156699
format_se	Elektronische Bücher
countryofpublication_str_mv	XA-DE-HH
author-letter	Harder, Dorian
normlink	RVK/156699: 4113937-9 105825778 209480580 122059360 70575572X 29307089X 1271600641 201600641 2021.11.09
normlink_prefix_str_mv	(DE-625)rvk/156699: (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 (DE-588)122059360 (DE-627)70575572X (DE-576)29307089X (DE-627)1271600641 (DE-576)201600641 2021.11.09
dewey-full	621.384191 004 621.3
author2-role	akademischer betreuerin Grad-verleihende Institution
title_sort	particle filtering with geospatial analysis for indoor positioning
title_auth	Particle Filtering with Geospatial Analysis for Indoor Positioning
abstract	Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods.
abstractGer	Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods.
abstract_unstemmed	Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods.
collection_details	GBV-ODiss GBV_ILN_370 ISIL_DE-1373 SYSFLAG_1 GBV_KXP GBV_ILN_2403 ISIL_DE-LFER
title_short	Particle Filtering with Geospatial Analysis for Indoor Positioning
url	https://repos.hcu-hamburg.de/handle/hcu/590 https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426 https://d-nb.info/1243507659/34
ausleihindikator_str_mv	370 2403:n
rolewithnormlink_str_mv	@@655@@(DE-588)4113937-9 @@dgs@@(DE-588)122059360
remote_bool	true
author2	Sternberg, Harald 1963- Shoushtari, Hossein HafenCity Universität Hamburg Institut für Geodäsie und Geoinformatik
author2Str	Sternberg, Harald 1963- Shoushtari, Hossein HafenCity Universität Hamburg Institut für Geodäsie und Geoinformatik
GND_str_mv	Hochschulschrift Sternberg, Harald
GND_txt_mv	Hochschulschrift Sternberg, Harald
GND_txtF_mv	Hochschulschrift Sternberg, Harald
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	true
author2_role	dgs dgs
callnumber-a	--%%--
up_date	2024-07-04T20:11:43.883Z
_version_	1803680642640117760
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000cam a2200265 4500</leader><controlfield tag="001">1776437985</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230810132526.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">211109s2021 gw \|\|\|\|\|om 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">urn:nbn:de:gbv:1373-repos-7426</subfield><subfield code="2">urn</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)1776437985</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KXP1776437985</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="c">XA-DE-HH</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">621.384191</subfield><subfield code="q">DE-101</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">004</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">621.3</subfield><subfield code="q">DE-101</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ZI 9070</subfield><subfield code="2">rvk</subfield><subfield code="0">(DE-625)rvk/156699:</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Harder, Dorian</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Particle Filtering with Geospatial Analysis for Indoor Positioning</subfield><subfield code="c">Dorian Harder</subfield></datafield><datafield tag="247" ind1="1" ind2="0"><subfield code="a">Partikel-Filter mit Geodaten-Analyse für die Indoor Positionierung</subfield><subfield code="f">Übers. des Hauptsacht.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hamburg</subfield><subfield code="b">HafenCity Universität Hamburg</subfield><subfield code="c">2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="b">Masterarbeit</subfield><subfield code="c">HafenCity Universität Hamburg, Institut für Geodäsie und Geoinformatik</subfield><subfield code="d">2021</subfield></datafield><datafield tag="506" ind1="0" ind2=" "><subfield code="q">DE-1373</subfield><subfield code="a">Open Access</subfield><subfield code="e">Controlled Vocabulary for Access Rights</subfield><subfield code="u">http://purl.org/coar/access_right/c_abf2</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Modern smartphones enable a wide range of people the use of location based services, such as personal navigation, in everyday life. The localisation in outdoor scenarios with smartphones is usually based on Global Navigation Satellite System (GNSS). However, the positioning with GNSS fails to provide sufficient and accurate measurements in an indoor environment. To enable the usage of location based services, for example the navigation at exhibition or airport areas or large university buildings, other indoor positioning approaches have been researched. Most of those can’t provide the needed accuracy or are expensive to install and maintain. A possible alternative is the usage of the Inertial Measurement Unit (IMU) of the smartphone using a pedestrian dead reckoning system Pedestrian Dead Reckoning (PDR). To correct the drift of the position estimate that results from noisy measurements, corrections through additional information is necessary. For this reason, two Particle Filter (PF) methods, a simple bootstrap PF and a backtracking PF, have been developed in this thesis. They both use building information from floor plans and routing edges, to improve the position estimate. The PF uses weighted particles to represent the probability density of the position estimate. The backtracking PF further stores the propagation history that can be used for further improvements of the position estimate. One novelty of the developed PF methods is the usage of geospatial analysis tools to derive information about the spatial relation between the particles and the geometries from the building information. The implementation of geospatial analysis tools further enables the use of geodata, which can be derived from building plans in Computer Aided Design software (CAD) format. The developed PF methods have been tested and compared with different methods for the weighting of particles regarding their positioning accuracy on two different test paths through the HafenCity University (HCU)-building in Hamburg. It was possible to achieve a position error of less than 3 m for a path through narrow corridors and less than 5.5 m for a path including wider spaces, such as hallways, 90 % of the time for some of the tested methods.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="q">DE-1373</subfield><subfield code="a">Namensnennung 3.0 International</subfield><subfield code="f">CC BY 3.0</subfield><subfield code="2">cc</subfield><subfield code="u">https://creativecommons.org/licenses/by/3.0/</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Particle filter</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">indoor positioning</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">smartphone</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Partikelfilter</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Geodatenanalyse</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Indoor-Positionierung</subfield><subfield code="2">DSpace</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="a">Hochschulschrift</subfield><subfield code="0">(DE-588)4113937-9</subfield><subfield code="0">(DE-627)105825778</subfield><subfield code="0">(DE-576)209480580</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sternberg, Harald</subfield><subfield code="d">1963-</subfield><subfield code="e">akademischer betreuerin</subfield><subfield code="0">(DE-588)122059360</subfield><subfield code="0">(DE-627)70575572X</subfield><subfield code="0">(DE-576)29307089X</subfield><subfield code="4">dgs</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shoushtari, Hossein</subfield><subfield code="e">akademischer betreuerin</subfield><subfield code="4">dgs</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">HafenCity Universität Hamburg</subfield><subfield code="b">Institut für Geodäsie und Geoinformatik</subfield><subfield code="e">Grad-verleihende Institution</subfield><subfield code="4">dgg</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://repos.hcu-hamburg.de/handle/hcu/590</subfield><subfield code="v">2021-11-17</subfield><subfield code="x">Resolving-System</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://nbn-resolving.org/urn:nbn:de:gbv:1373-repos-7426</subfield><subfield code="v">2021-11-17</subfield><subfield code="x">Resolving-System</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://d-nb.info/1243507659/34</subfield><subfield code="v">2021-11-17</subfield><subfield code="x">Langzeitarchivierung Nationalbibliothek</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV-ODiss</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ISIL_DE-1373</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_1</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_KXP</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2403</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ISIL_DE-LFER</subfield></datafield><datafield tag="935" ind1=" " ind2=" "><subfield code="i">DSpace</subfield></datafield><datafield tag="936" ind1="r" ind2="v"><subfield code="a">ZI 9070</subfield><subfield code="b">Geodätisches Messen, Messverfahren</subfield><subfield code="k">Technik</subfield><subfield code="k">Bauingenieurwesen</subfield><subfield code="k">Geodäsie, Vermessung</subfield><subfield code="k">Geodätisches Messen, Messverfahren</subfield><subfield code="0">(DE-627)1271600641</subfield><subfield code="0">(DE-625)rvk/156699:</subfield><subfield code="0">(DE-576)201600641</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">621.384191</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">004</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="b">3999998768</subfield><subfield code="h">olr-stud</subfield><subfield code="y">z</subfield><subfield code="z">09-11-21</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">2403</subfield><subfield code="1">01</subfield><subfield code="x">DE-LFER</subfield><subfield code="b">4014652718</subfield><subfield code="c">00</subfield><subfield code="f">--%%--</subfield><subfield code="d">--%%--</subfield><subfield code="e">n</subfield><subfield code="j">--%%--</subfield><subfield code="y">l01</subfield><subfield code="z">06-12-21</subfield></datafield><datafield tag="981" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="r">https://repos.hcu-hamburg.de/handle/hcu/590</subfield></datafield><datafield tag="981" ind1=" " ind2=" "><subfield code="2">2403</subfield><subfield code="1">01</subfield><subfield code="x">DE-LFER</subfield><subfield code="r">https://repos.hcu-hamburg.de/handle/hcu/590</subfield></datafield><datafield tag="995" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="a">olr-stud</subfield></datafield><datafield tag="995" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="a">olr-free</subfield></datafield><datafield tag="998" ind1=" " ind2=" "><subfield code="2">370</subfield><subfield code="1">01</subfield><subfield code="x">4370</subfield><subfield code="0">2021.11.09</subfield></datafield></record></collection>
score	7.3985147

Nicht das Richtige dabei?

Schreiben Sie uns!

Particle Filtering with Geospatial Analysis for Indoor Positioning

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?