• DocumentCode
    527449
  • Title

    Multi-sensor information fusion based on BP network

  • Author

    Li, Guoyu

  • Author_Institution
    Sch. of Phys. & Optoelectron. Eng., Dalian Univ. of Technol., Dalian, China
  • Volume
    3
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    1442
  • Lastpage
    1445
  • Abstract
    The output of pressure sensor is affected by non-objection parameters in its application, such as temperature, power fluctuation and so on. Multi-sensor information fusion based on BP network can eliminate the side effect of non-objection parameters and improve the accuracy and reliability for the pressure sensor. This method based on LMBP algorithm of BP network has not only a simple network structure, but also a quick learning rate, showing a better prospect. The paper describes the LMBP algorithm, deduces the matrix formula of the two-layer network, and makes use of LMBP algorithm to fuse the temperature, power fluctuation and pressure information of the pressure sensor. Finally the paper fuses the example data of the pressure sensor with the help of the MATLAB software and draws a conclusion that the LMBP algorithm eliminates easily the affection of the non-objection parameters and improves the accuracy of the pressure sensor.
  • Keywords
    backpropagation; matrix algebra; neural nets; pressure sensors; sensor fusion; BP network; LMBP algorithm; MATLAB software; matrix formula; multisensor information fusion; power fluctuation; pressure sensor; temperature; Accuracy; Artificial neural networks; Equations; Fluctuations; Mathematical model; Temperature sensors; Training; BP network; algorithm; information fusion; pressure sensor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5582862
  • Filename
    5582862