Inertial Pocket Navigation System: Unaided 3D Positioning
Inertial navigation systems use dead-reckoning to estimate the pedestrian’s position. There are two types of pedestrian dead-reckoning, the strapdown algorithm and the step-and-heading approach. Unlike the strapdown algorithm, which consists of the double integration of the three orthogonal accelero...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/15/4/9156 |
| _version_ | 1798039351013146624 |
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| author | Estefania Munoz Diaz |
| author_facet | Estefania Munoz Diaz |
| author_sort | Estefania Munoz Diaz |
| collection | DOAJ |
| description | Inertial navigation systems use dead-reckoning to estimate the pedestrian’s position. There are two types of pedestrian dead-reckoning, the strapdown algorithm and the step-and-heading approach. Unlike the strapdown algorithm, which consists of the double integration of the three orthogonal accelerometer readings, the step-and-heading approach lacks the vertical displacement estimation. We propose the first step-and-heading approach based on unaided inertial data solving 3D positioning. We present a step detector for steps up and down and a novel vertical displacement estimator. Our navigation system uses the sensor introduced in the front pocket of the trousers, a likely location of a smartphone. The proposed algorithms are based on the opening angle of the leg or pitch angle. We analyzed our step detector and compared it with the state-of-the-art, as well as our already proposed step length estimator. Lastly, we assessed our vertical displacement estimator in a real-world scenario. We found that our algorithms outperform the literature step and heading algorithms and solve 3D positioning using unaided inertial data. Additionally, we found that with the pitch angle, five activities are distinguishable: standing, sitting, walking, walking up stairs and walking down stairs. This information complements the pedestrian location and is of interest for applications, such as elderly care. |
| first_indexed | 2024-04-11T21:52:41Z |
| format | Article |
| id | doaj.art-efcbd30251044c988e05e741e8f6d875 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:52:41Z |
| publishDate | 2015-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-efcbd30251044c988e05e741e8f6d8752022-12-22T04:01:12ZengMDPI AGSensors1424-82202015-04-011549156917810.3390/s150409156s150409156Inertial Pocket Navigation System: Unaided 3D PositioningEstefania Munoz Diaz0German Aerospace Center (DLR), Institute of Communications and Navigation, Oberpfaffenhofen, 82234 Wessling, GermanyInertial navigation systems use dead-reckoning to estimate the pedestrian’s position. There are two types of pedestrian dead-reckoning, the strapdown algorithm and the step-and-heading approach. Unlike the strapdown algorithm, which consists of the double integration of the three orthogonal accelerometer readings, the step-and-heading approach lacks the vertical displacement estimation. We propose the first step-and-heading approach based on unaided inertial data solving 3D positioning. We present a step detector for steps up and down and a novel vertical displacement estimator. Our navigation system uses the sensor introduced in the front pocket of the trousers, a likely location of a smartphone. The proposed algorithms are based on the opening angle of the leg or pitch angle. We analyzed our step detector and compared it with the state-of-the-art, as well as our already proposed step length estimator. Lastly, we assessed our vertical displacement estimator in a real-world scenario. We found that our algorithms outperform the literature step and heading algorithms and solve 3D positioning using unaided inertial data. Additionally, we found that with the pitch angle, five activities are distinguishable: standing, sitting, walking, walking up stairs and walking down stairs. This information complements the pedestrian location and is of interest for applications, such as elderly care.http://www.mdpi.com/1424-8220/15/4/9156step lengthstep detectorattitudepedestriandead reckoningorientationpitchvertical displacementactivity |
| spellingShingle | Estefania Munoz Diaz Inertial Pocket Navigation System: Unaided 3D Positioning Sensors step length step detector attitude pedestrian dead reckoning orientation pitch vertical displacement activity |
| title | Inertial Pocket Navigation System: Unaided 3D Positioning |
| title_full | Inertial Pocket Navigation System: Unaided 3D Positioning |
| title_fullStr | Inertial Pocket Navigation System: Unaided 3D Positioning |
| title_full_unstemmed | Inertial Pocket Navigation System: Unaided 3D Positioning |
| title_short | Inertial Pocket Navigation System: Unaided 3D Positioning |
| title_sort | inertial pocket navigation system unaided 3d positioning |
| topic | step length step detector attitude pedestrian dead reckoning orientation pitch vertical displacement activity |
| url | http://www.mdpi.com/1424-8220/15/4/9156 |
| work_keys_str_mv | AT estefaniamunozdiaz inertialpocketnavigationsystemunaided3dpositioning |