Artificial Neural Networks in an Inertial Measurement Unit
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU119242" target="_blank" >RIV/00216305:26220/16:PU119242 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/7477431" target="_blank" >https://ieeexplore.ieee.org/document/7477431</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/RADIOELEK.2016.7477431" target="_blank" >10.1109/RADIOELEK.2016.7477431</a>
Alternative languages
Result language
angličtina
Original language name
Artificial Neural Networks in an Inertial Measurement Unit
Original language description
This paper presents an effective method combining classic data processing using a simple MEMS inertial measurement unit (IMU) and an artificial neural network (AAN) to achieve more accurate pedestrian positioning. Generally, this application based on a standard IMU without support from another system, such as satellite navigation, is characterized by poorly estimating position and orientation, wherein the positioning error grows over time. The proposed approach uses an artificial neural network, which is designed to determine the status of "what is happening" with the body of the IMU. Two possible statuses are considered. The first of these is the fact that the IMU is static, regardless of its orientation, and the second state is a man walking with an IMU placed on his body. In principal, further statuses can be added to the classification results from the ANN, e.g. jogging, driving, shaking, spinning, flying, falling etc. This paper not only presents the theoretical but also a series of experiments. It has been demonstrated that the proposed approach improves personal tracking accuracy by more than ten times compared to the application of an unaided IMU.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20202 - Communication engineering and systems
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 26th International Conference RADIOELEKTRONIKA 2016
ISBN
978-1-5090-1673-0
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
176-180
Publisher name
Neuveden
Place of publication
Neuveden
Event location
Košice
Event date
Apr 19, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000383741100036