A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial Sensors
The zero-velocity update (ZUPT) algorithm is a pivotal advancement in pedestrian navigation accuracy, utilizing foot-mounted inertial sensors. Its key issue hinges on accurately identifying periods of zero-velocity during human movement. This paper introduces an innovative adaptive sliding window te...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/3/838 |
| _version_ | 1797318285591576576 |
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| author | Xiaotao Wang Jiacheng Li Guangfei Xu Xingyu Wang |
| author_facet | Xiaotao Wang Jiacheng Li Guangfei Xu Xingyu Wang |
| author_sort | Xiaotao Wang |
| collection | DOAJ |
| description | The zero-velocity update (ZUPT) algorithm is a pivotal advancement in pedestrian navigation accuracy, utilizing foot-mounted inertial sensors. Its key issue hinges on accurately identifying periods of zero-velocity during human movement. This paper introduces an innovative adaptive sliding window technique, leveraging the Fourier Transform to precisely isolate the pedestrian’s gait frequency from spectral data. Building on this, the algorithm adaptively adjusts the zero-velocity detection threshold in accordance with the identified gait frequency. This adaptation significantly refines the accuracy in detecting zero-velocity intervals. Experimental evaluations reveal that this method outperforms traditional fixed-threshold approaches by enhancing precision and minimizing false positives. Experiments on single-step estimation show the adaptability of the algorithm to motion states such as slow, fast, and running. Additionally, the paper demonstrates pedestrian trajectory localization experiments under a variety of walking conditions. These tests confirm that the proposed method substantially improves the performance of the ZUPT algorithm, highlighting its potential for pedestrian navigation systems. |
| first_indexed | 2024-03-08T03:49:14Z |
| format | Article |
| id | doaj.art-d66146c4b0234656b2c78801d6ca2832 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T03:49:14Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d66146c4b0234656b2c78801d6ca28322024-02-09T15:22:00ZengMDPI AGSensors1424-82202024-01-0124383810.3390/s24030838A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial SensorsXiaotao Wang0Jiacheng Li1Guangfei Xu2Xingyu Wang3College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaCollege of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaCollege of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaCollege of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaThe zero-velocity update (ZUPT) algorithm is a pivotal advancement in pedestrian navigation accuracy, utilizing foot-mounted inertial sensors. Its key issue hinges on accurately identifying periods of zero-velocity during human movement. This paper introduces an innovative adaptive sliding window technique, leveraging the Fourier Transform to precisely isolate the pedestrian’s gait frequency from spectral data. Building on this, the algorithm adaptively adjusts the zero-velocity detection threshold in accordance with the identified gait frequency. This adaptation significantly refines the accuracy in detecting zero-velocity intervals. Experimental evaluations reveal that this method outperforms traditional fixed-threshold approaches by enhancing precision and minimizing false positives. Experiments on single-step estimation show the adaptability of the algorithm to motion states such as slow, fast, and running. Additionally, the paper demonstrates pedestrian trajectory localization experiments under a variety of walking conditions. These tests confirm that the proposed method substantially improves the performance of the ZUPT algorithm, highlighting its potential for pedestrian navigation systems.https://www.mdpi.com/1424-8220/24/3/838pedestrian navigationadaptive thresholdingzero-velocity interval detectiongait frequency analysisZUPT algorithm |
| spellingShingle | Xiaotao Wang Jiacheng Li Guangfei Xu Xingyu Wang A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial Sensors Sensors pedestrian navigation adaptive thresholding zero-velocity interval detection gait frequency analysis ZUPT algorithm |
| title | A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial Sensors |
| title_full | A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial Sensors |
| title_fullStr | A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial Sensors |
| title_full_unstemmed | A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial Sensors |
| title_short | A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial Sensors |
| title_sort | novel zero velocity interval detection algorithm for a pedestrian navigation system with foot mounted inertial sensors |
| topic | pedestrian navigation adaptive thresholding zero-velocity interval detection gait frequency analysis ZUPT algorithm |
| url | https://www.mdpi.com/1424-8220/24/3/838 |
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