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Research Article
Venkata Krishnaveni B
JNTUA: Jawaharlal Nehru Technological University Anantapur
Corresponding Author
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In recent days Internet of Things (IoT) applications becoming prominent, like smart home, connected health, smart farming, smart retail and smart manufacturing, will lead to a challenging task in providing low cost, high precision localization and tracking in indoor environments. Positioning in indoor is yet an open issue mostly because of not receiving the signals of GPS in the context of indoor. Inertial Measurement Unit (IMU) can give an exact indoor tracking, however, they regularly experience the cumulated error as the speed and position are gotten by incorporating the increasing acceleration constantly as for time. At the same time Ultra Wideband (UWB) localization and tracking will be influenced by the real time indoor conditions. It is difficult to utilize an independent localization and tracking system to accomplish high precision in indoor conditions. In this paper, we come up with an incorporated positioning system in indoor by joining IMU and the UWB over the Unscented Kalman Filter (UKF) and the Extended Kalman Filter (EKF) to enhance the precision. All these algorithms are analyzed and assessed dependent on their exhibition.
Keywords
Extended Kalman Filter, Indoor positioning, IoT, Ultra Wideband, IMU, Unscented Kalman Filter
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Posted 24 Mar, 2021
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This preprint is under consideration at Wireless Personal Communications. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Venkata Krishnaveni B
JNTUA: Jawaharlal Nehru Technological University Anantapur
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 24 Mar, 2021
No community comments so far
Review #? received
Received 22 Mar, 2021
Reviewers invited
Invitations sent on 21 Mar, 2021
First submitted
On 21 Jan, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Technical Communication
License:
This work is licensed under a CC BY 4.0 License. Read Full License
In recent days Internet of Things (IoT) applications becoming prominent, like smart home, connected health, smart farming, smart retail and smart manufacturing, will lead to a challenging task in providing low cost, high precision localization and tracking in indoor environments. Positioning in indoor is yet an open issue mostly because of not receiving the signals of GPS in the context of indoor. Inertial Measurement Unit (IMU) can give an exact indoor tracking, however, they regularly experience the cumulated error as the speed and position are gotten by incorporating the increasing acceleration constantly as for time. At the same time Ultra Wideband (UWB) localization and tracking will be influenced by the real time indoor conditions. It is difficult to utilize an independent localization and tracking system to accomplish high precision in indoor conditions. In this paper, we come up with an incorporated positioning system in indoor by joining IMU and the UWB over the Unscented Kalman Filter (UKF) and the Extended Kalman Filter (EKF) to enhance the precision. All these algorithms are analyzed and assessed dependent on their exhibition.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
This preprint is available for download as a PDF.
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