Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind Environment
Aiming at the long-term cumulative error inherent in pedestrian indoor inertial positioning filed, that error is mainly due to the low signal-to-noise ratio of the sensor output signal quality, the temperature drift of the gyro and the accuracy of error estimation. This paper proposes a new optimiza...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9028220/ |
| _version_ | 1818854662108872704 |
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| author | Hengzhi Liu Qing Li Chao Li Hui Zhao |
| author_facet | Hengzhi Liu Qing Li Chao Li Hui Zhao |
| author_sort | Hengzhi Liu |
| collection | DOAJ |
| description | Aiming at the long-term cumulative error inherent in pedestrian indoor inertial positioning filed, that error is mainly due to the low signal-to-noise ratio of the sensor output signal quality, the temperature drift of the gyro and the accuracy of error estimation. This paper proposes a new optimization method for array distributed MEMS-IMU: this method performs filtering and noise reduction optimization processing on inertial sensor data; The effect of temperature on the gyroscope is reduced by matrix-optimized layout, and distributed temperature compensation is performed for eight IMUs. We used MEMS-IMU worn on the foot finishing the data acquisition. Then improved a novel Pearson coefficient particle filtering method to finally complete the information fusion and positioning process in a blind environment (no beacon auxiliary information) high-precision personal large span (long time span, large distance span). The indoor positioning test results in the No. 6 Office Building of National Defense Science and Technology Park in Beijing Institute of Technology verify that the method has a horizontal error of only 6.23m (TTD ≈ 0.52%) during the horizontal span positioning which the total distance is about 1200m; In terms of vertical largespan positioning accuracy: the height error is only 4.56m (TTD ≈ 7.6%) during the positioning process of 68 minutes and 35 seconds (including intermediate stop). Compared with other multi-IMU personal positioning optimization methods, it has the advantages of high sensor data quality, small gyro temperature influence, good system error estimation accuracy and long-term long-distance positioning results. It provides a good and reliable theoretical reference for this field or extension applications. |
| first_indexed | 2024-12-19T07:56:16Z |
| format | Article |
| id | doaj.art-8ba7dedc1c8b4a119d4b7c46a38bfa82 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T07:56:16Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8ba7dedc1c8b4a119d4b7c46a38bfa822022-12-21T20:30:00ZengIEEEIEEE Access2169-35362020-01-018481634817610.1109/ACCESS.2020.29794849028220Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind EnvironmentHengzhi Liu0https://orcid.org/0000-0001-7014-4139Qing Li1Chao Li2https://orcid.org/0000-0002-0642-7334Hui Zhao3https://orcid.org/0000-0002-5326-9930School of Automation, Beijing Information Science and Technology University, Beijing, ChinaSchool of Automation, Beijing Information Science and Technology University, Beijing, ChinaBeijing Key Laboratory of High Dynamic Navigation Technology, Beijing Information Science and Technology University, Beijing, ChinaBeijing Key Laboratory of High Dynamic Navigation Technology, Beijing Information Science and Technology University, Beijing, ChinaAiming at the long-term cumulative error inherent in pedestrian indoor inertial positioning filed, that error is mainly due to the low signal-to-noise ratio of the sensor output signal quality, the temperature drift of the gyro and the accuracy of error estimation. This paper proposes a new optimization method for array distributed MEMS-IMU: this method performs filtering and noise reduction optimization processing on inertial sensor data; The effect of temperature on the gyroscope is reduced by matrix-optimized layout, and distributed temperature compensation is performed for eight IMUs. We used MEMS-IMU worn on the foot finishing the data acquisition. Then improved a novel Pearson coefficient particle filtering method to finally complete the information fusion and positioning process in a blind environment (no beacon auxiliary information) high-precision personal large span (long time span, large distance span). The indoor positioning test results in the No. 6 Office Building of National Defense Science and Technology Park in Beijing Institute of Technology verify that the method has a horizontal error of only 6.23m (TTD ≈ 0.52%) during the horizontal span positioning which the total distance is about 1200m; In terms of vertical largespan positioning accuracy: the height error is only 4.56m (TTD ≈ 7.6%) during the positioning process of 68 minutes and 35 seconds (including intermediate stop). Compared with other multi-IMU personal positioning optimization methods, it has the advantages of high sensor data quality, small gyro temperature influence, good system error estimation accuracy and long-term long-distance positioning results. It provides a good and reliable theoretical reference for this field or extension applications.https://ieeexplore.ieee.org/document/9028220/Array distributionMEMS-IMUfiltering noise reductionoptimized layoutmulti-channel temperature compensationimproved Pearson coefficient particle filter |
| spellingShingle | Hengzhi Liu Qing Li Chao Li Hui Zhao Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind Environment IEEE Access Array distribution MEMS-IMU filtering noise reduction optimized layout multi-channel temperature compensation improved Pearson coefficient particle filter |
| title | Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind Environment |
| title_full | Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind Environment |
| title_fullStr | Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind Environment |
| title_full_unstemmed | Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind Environment |
| title_short | Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind Environment |
| title_sort | application research of an array distributed imu optimization processing method in personal positioning in large span blind environment |
| topic | Array distribution MEMS-IMU filtering noise reduction optimized layout multi-channel temperature compensation improved Pearson coefficient particle filter |
| url | https://ieeexplore.ieee.org/document/9028220/ |
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