• DocumentCode
    31873
  • Title

    Hybrid Approach for Unbiased Coherence Estimation for Multitemporal InSAR

  • Author

    Mi Jiang ; Xiaoli Ding ; Zhiwei Li

  • Author_Institution
    Dept. of Land Surveying & Geo-Inf., Hong Kong Polytech. Univ., Hong Kong, China
  • Volume
    52
  • Issue
    5
  • fYear
    2014
  • fDate
    May-14
  • Firstpage
    2459
  • Lastpage
    2473
  • Abstract
    The coherence of radar echoes is a fundamental observable in interferometric synthetic aperture radar (InSAR) measurements. It provides a quantitative measure of the scattering properties of imaged surfaces and therefore is widely applied to study the physical processes of the Earth. However, unfortunately, the estimated coherence values are often biased due to various reasons such as radar signal nonstationarity and the bias in the estimators used. In this paper, we focus on multitemporal InSAR coherence estimation and present a hybrid approach that mitigates effectively the errors in the estimation. The proposed approach is almost completely self-adaptive and workable for both Gaussian and non-Gaussian SAR scenes. Moreover, the bias of the sample coherence can be mitigated with even only several samples included for a given pixel. Therefore, it is a more pragmatic method for accurate coherence estimation and can be applied actually. Different data sets are used to test the proposed method and demonstrate its advantages.
  • Keywords
    radar interferometry; synthetic aperture radar; Gaussian SAR scenes; hybrid approach; interferometric SAR measurements; multitemporal InSAR coherence estimation; multitemporal InSAR measurements; pragmatic method; radar echoes; radar signal nonstationarity; synthetic aperture radar; unbiased coherence estimation; Accuracy; Coherence; Estimation; Feature extraction; Synthetic aperture radar; Vectors; Adaptive hypothesis test; bootstrap; coherence estimation; fringe rate estimation; interferometric synthetic aperture radar (InSAR);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2013.2261996
  • Filename
    6557041