• DocumentCode
    1408764
  • Title

    Identifying Fabrics With a Variable Emission Airborne Spiking Sonar

  • Author

    Álvarez, Fernando J. ; Kuc, Roman ; Aguilera, Teodoro

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Extremadura, Badajoz, Spain
  • Volume
    11
  • Issue
    9
  • fYear
    2011
  • Firstpage
    1905
  • Lastpage
    1912
  • Abstract
    A new spiking sonar based on the commercial 6500 module is presented in this work that, unlike the previous versions of this sensor, is capable to vary both the duration and the frequency of its emission. This feature is provided by a PIC18F452 device that also controls the module integrator to generate the sequence of spikes whose density is proportional to the amplitude of the echo. The sensor is used to generate rotational scans of a post covered with different fabrics at six different frequencies. Principal component analysis applied to the number of spikes obtained at different bearings and frequencies generates datasets that are clearly separated for each material, thus facilitating their latter identification by means of a probabilistic neural network.
  • Keywords
    fabrics; principal component analysis; sonar; fabrics; module integrator; principal component analysis; probabilistic neural network; variable emission airborne spiking sonar; Distance measurement; Fabrics; Principal component analysis; Sensors; Sonar; Transducers; Fabrics identification; principal component analysis (PCA); probabilistic neural network; spiking sonar;
  • fLanguage
    English
  • Journal_Title
    Sensors Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1530-437X
  • Type

    jour

  • DOI
    10.1109/JSEN.2010.2100817
  • Filename
    5672568