Enhancement Of Wifi Indoor Positioning System
There are many Location-Based Systems (LBS) that have been implemented in indoor envi- ronments using different wireless technologies, although they lacks the estimation accuracy and their hardware infrastructure and their setup costs are very high. The need for an indoor positioning system that...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.usm.my/49013/1/Ahed%20Aboodi_HJ.pdf |
| _version_ | 1797012117291794432 |
|---|---|
| author | Aboodi, Ahed Hussein |
| author_facet | Aboodi, Ahed Hussein |
| author_sort | Aboodi, Ahed Hussein |
| collection | USM |
| description | There are many Location-Based Systems (LBS) that have been implemented in indoor envi-
ronments using different wireless technologies, although they lacks the estimation accuracy
and their hardware infrastructure and their setup costs are very high. The need for an indoor
positioning system that uses the existing infrastructure (WiFi) of a building and achieves a high
accuracy positioning is therefore, required.
In this research, a new algorithm named (WBI) is proposed, based on the WiFi Received
Signal Strength (RSS) technology. The algorithm calculates the distances from the RSSs col-
lected around the area, and checks for an error occurrence after the location estimation is calcu-
lated with Least Square Algorithm (LSA). The estimated location is checked wether it is inside
the bounding box constructed by the Min-Max algorithm, if so, a Kalman filter is applied which
in turn fixes the distance that falls under non-line-of-sight condition (that caused the error), and
after that, the estimated location is recalculated with the corrected distances using LSA.
Some experiments were performed in the School of Computer Sciences in Universiti Sains
Malaysia before implementing the proposed algorithm. These experiments include determin-
ing and calculating the factors used for distance estimation and the wall penetration effect. The
proposed algorithm has achieved an average accuracy of 2:6m for maximum mobility move-
ment speed of 0:80m=s, and has been evaluated against other two trilateration algorithms (LSA
Corrected and LSA No Correction) which have archived the average accuracy of 34:32m and
218:35m respectively. |
| first_indexed | 2024-03-06T15:43:31Z |
| format | Thesis |
| id | usm.eprints-49013 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2024-03-06T15:43:31Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | usm.eprints-490132021-04-26T07:07:59Z http://eprints.usm.my/49013/ Enhancement Of Wifi Indoor Positioning System Aboodi, Ahed Hussein QA75.5-76.95 Electronic computers. Computer science There are many Location-Based Systems (LBS) that have been implemented in indoor envi- ronments using different wireless technologies, although they lacks the estimation accuracy and their hardware infrastructure and their setup costs are very high. The need for an indoor positioning system that uses the existing infrastructure (WiFi) of a building and achieves a high accuracy positioning is therefore, required. In this research, a new algorithm named (WBI) is proposed, based on the WiFi Received Signal Strength (RSS) technology. The algorithm calculates the distances from the RSSs col- lected around the area, and checks for an error occurrence after the location estimation is calcu- lated with Least Square Algorithm (LSA). The estimated location is checked wether it is inside the bounding box constructed by the Min-Max algorithm, if so, a Kalman filter is applied which in turn fixes the distance that falls under non-line-of-sight condition (that caused the error), and after that, the estimated location is recalculated with the corrected distances using LSA. Some experiments were performed in the School of Computer Sciences in Universiti Sains Malaysia before implementing the proposed algorithm. These experiments include determin- ing and calculating the factors used for distance estimation and the wall penetration effect. The proposed algorithm has achieved an average accuracy of 2:6m for maximum mobility move- ment speed of 0:80m=s, and has been evaluated against other two trilateration algorithms (LSA Corrected and LSA No Correction) which have archived the average accuracy of 34:32m and 218:35m respectively. 2011-06 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/49013/1/Ahed%20Aboodi_HJ.pdf Aboodi, Ahed Hussein (2011) Enhancement Of Wifi Indoor Positioning System. Masters thesis, Universiti Sains Malaysia. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Aboodi, Ahed Hussein Enhancement Of Wifi Indoor Positioning System |
| title | Enhancement Of Wifi Indoor Positioning
System |
| title_full | Enhancement Of Wifi Indoor Positioning
System |
| title_fullStr | Enhancement Of Wifi Indoor Positioning
System |
| title_full_unstemmed | Enhancement Of Wifi Indoor Positioning
System |
| title_short | Enhancement Of Wifi Indoor Positioning
System |
| title_sort | enhancement of wifi indoor positioning system |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/49013/1/Ahed%20Aboodi_HJ.pdf |
| work_keys_str_mv | AT aboodiahedhussein enhancementofwifiindoorpositioningsystem |