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Neural Network and Kalman Filter Use for Improvement of Inertial Distance Determination

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Man–Machine Interactions 4

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 391))

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Abstract

Appropriate distance estimation is very important in different applications, e.g. in navigation or developing natural interfaces for man-machine interaction. Article refers to this problem and presents two approaches in improving estimation of the distance. The distance is computed on the base of linear acceleration. The acceleration data is captured by an inertial sensor mounted on moving object. The first approach uses Kalman filter and appropriate preprocessing steps to denoise measured acceleration. This method improves the distance estimation in noticeable manner but is not optimal because of time growing errors. These errors results come from the imperfection of the accelerometer and double integration of acceleration data during computational step. The second approach improves the estimation accuracy by using a neural network. The neural network estimates position of moving object on the base of statistical properties of the acceleration signal. Both of mentioned approaches were compared and the results are described in this article. Theoretical contemplation was confirmed by practical verification which results are also presented. Conducted research show that these two approaches can be combined for an optimal problem solution.

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Authors and Affiliations

  1. Institute of Computer Science, Lublin University of Technology, Lublin, Poland

    Piotr Kopniak & Marek Kaminski

Authors
  1. Piotr Kopniak
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  2. Marek Kaminski
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Corresponding author

Correspondence to Piotr Kopniak .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Brachman

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

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Kopniak, P., Kaminski, M. (2016). Neural Network and Kalman Filter Use for Improvement of Inertial Distance Determination. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-23437-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23436-6

  • Online ISBN: 978-3-319-23437-3

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