• DocumentCode
    2520455
  • Title

    A new method based on the BP neural network to improve the accuracy of inversion of the vegetation height

  • Author

    Tingwei, Li ; Diannong, Liang ; HaiFeng, Huang ; Jubo, Zhu

  • Author_Institution
    Coll. of Electron., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2010
  • fDate
    9-11 April 2010
  • Firstpage
    544
  • Lastpage
    547
  • Abstract
    The error in the estimation of the ground interferometric phase will reduce the accuracy of the inversion of the vegetation height in three-stage vegetation inversion method. Aiming at this problem, the new vegetation height inversion method based on the BP neural network is proposed. The new method directly fits the nonlinear mapping relationship between the complex correction coefficients and the vegetation height, so it reduces the height inversion error caused by the error in the estimated ground interferometric phase. The new method has better performance than the three-stage vegetation height inversion method, and the experiment results validate the superiority of the new method.
  • Keywords
    interferometry; neural nets; radar polarimetry; synthetic aperture radar; vegetation mapping; BP neural network; ground interferometric phase; height inversion error; nonlinear mapping; polarimetric SAR interferometry; three-stage vegetation inversion method; vegetation height inversion; Coherence; Educational institutions; Electromagnetic scattering; Error correction; Estimation error; Flowcharts; Interferometry; Neural networks; Phase estimation; Vegetation mapping; BP neural network; polarimetric SAR interferometry; three-stage method; vegetation height inversion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Signal Processing (IASP), 2010 International Conference on
  • Conference_Location
    Zhejiang
  • Print_ISBN
    978-1-4244-5554-6
  • Electronic_ISBN
    978-1-4244-5556-0
  • Type

    conf

  • DOI
    10.1109/IASP.2010.5476059
  • Filename
    5476059