PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation
Providing an accurate and practical navigation solution anywhere with portable devices, such as smartphones, is still a challenge, especially in environments where global navigation satellite systems (GNSS) signals are not available or are degraded. This paper proposes a new algorithm that integrat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-06-01
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| Series: | Micromachines |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2072-666X/6/6/793 |
| _version_ | 1828232469882601472 |
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| author | Yuan Zhuang Haiyu Lan You Li Naser El-Sheimy |
| author_facet | Yuan Zhuang Haiyu Lan You Li Naser El-Sheimy |
| author_sort | Yuan Zhuang |
| collection | DOAJ |
| description | Providing an accurate and practical navigation solution anywhere with portable devices, such as smartphones, is still a challenge, especially in environments where global navigation satellite systems (GNSS) signals are not available or are degraded. This paper proposes a new algorithm that integrates inertial navigation system (INS) and pedestrian dead reckoning (PDR) to combine the advantages of both mechanizations for micro-electro-mechanical systems (MEMS) sensors in pedestrian navigation applications. In this PDR/INS integration algorithm, a pseudo-velocity-vector, which is composed of the PDR-derived forward speed and zero lateral and vertical speeds from non-holonomic constraints (NHC), works as an update for the INS to limit the velocity errors. To further limit the drift of MEMS inertial sensors, trilateration-based WiFi positions with small variances are also selected as updates for the PDR/INS integrated system. The experiments illustrate that positioning error is decreased by 60%–75% by using the proposed PDR/INS integrated MEMS solution when compared with PDR. The positioning error is further decreased by 15%–55% if the proposed PDR/INS/WiFi integrated solution is implemented. The average accuracy of the proposed PDR/INS/WiFi integration algorithm achieves 4.5 m in indoor environments. |
| first_indexed | 2024-04-12T19:23:45Z |
| format | Article |
| id | doaj.art-3a83b13b334d4ef89a9039ea78252a1e |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-04-12T19:23:45Z |
| publishDate | 2015-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-3a83b13b334d4ef89a9039ea78252a1e2022-12-22T03:19:32ZengMDPI AGMicromachines2072-666X2015-06-016679381210.3390/mi6060793mi6060793PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian NavigationYuan Zhuang0Haiyu Lan1You Li2Naser El-Sheimy3Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, CanadaDepartment of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, CanadaDepartment of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, CanadaDepartment of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, CanadaProviding an accurate and practical navigation solution anywhere with portable devices, such as smartphones, is still a challenge, especially in environments where global navigation satellite systems (GNSS) signals are not available or are degraded. This paper proposes a new algorithm that integrates inertial navigation system (INS) and pedestrian dead reckoning (PDR) to combine the advantages of both mechanizations for micro-electro-mechanical systems (MEMS) sensors in pedestrian navigation applications. In this PDR/INS integration algorithm, a pseudo-velocity-vector, which is composed of the PDR-derived forward speed and zero lateral and vertical speeds from non-holonomic constraints (NHC), works as an update for the INS to limit the velocity errors. To further limit the drift of MEMS inertial sensors, trilateration-based WiFi positions with small variances are also selected as updates for the PDR/INS integrated system. The experiments illustrate that positioning error is decreased by 60%–75% by using the proposed PDR/INS integrated MEMS solution when compared with PDR. The positioning error is further decreased by 15%–55% if the proposed PDR/INS/WiFi integrated solution is implemented. The average accuracy of the proposed PDR/INS/WiFi integration algorithm achieves 4.5 m in indoor environments.http://www.mdpi.com/2072-666X/6/6/793PDR/INS/WiFi integrationPDR/INS integrationpseudo-velocity updateindoor pedestrian navigationsmartphonemotion constraints |
| spellingShingle | Yuan Zhuang Haiyu Lan You Li Naser El-Sheimy PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation Micromachines PDR/INS/WiFi integration PDR/INS integration pseudo-velocity update indoor pedestrian navigation smartphone motion constraints |
| title | PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation |
| title_full | PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation |
| title_fullStr | PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation |
| title_full_unstemmed | PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation |
| title_short | PDR/INS/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation |
| title_sort | pdr ins wifi integration based on handheld devices for indoor pedestrian navigation |
| topic | PDR/INS/WiFi integration PDR/INS integration pseudo-velocity update indoor pedestrian navigation smartphone motion constraints |
| url | http://www.mdpi.com/2072-666X/6/6/793 |
| work_keys_str_mv | AT yuanzhuang pdrinswifiintegrationbasedonhandhelddevicesforindoorpedestriannavigation AT haiyulan pdrinswifiintegrationbasedonhandhelddevicesforindoorpedestriannavigation AT youli pdrinswifiintegrationbasedonhandhelddevicesforindoorpedestriannavigation AT naserelsheimy pdrinswifiintegrationbasedonhandhelddevicesforindoorpedestriannavigation |