• DocumentCode
    66150
  • Title

    RFI Mitigation Using Two-Scale Estimators for Statistical Variance

  • Author

    Goodberlet, M.A. ; Popstefanija, I.

  • Author_Institution
    ProSensing Inc., Amherst, MA, USA
  • Volume
    10
  • Issue
    4
  • fYear
    2013
  • fDate
    Jul-13
  • Firstpage
    721
  • Lastpage
    725
  • Abstract
    The well-known sample variance estimator utilizes N samples from a random process to first estimate the process mean. The estimator then uses the same N samples to estimate variance from this mean. Process variance could also be estimated by first using less than N samples to estimate the mean, followed by using all N samples to estimate variance. Two-scale estimators of this type, both causal and noncausal, are defined. Statistics for these estimators are derived, which are valid for samples from any statistical distribution. These statistics are used to improve analysis of a previously reported device called the double detector. In microwave radiometry, the double detector senses the presence of deterministic signals, often called radio-frequency interference, that corrupt the usual measurement consisting only of Planck radiation.
  • Keywords
    geophysical techniques; radiometry; random processes; statistical distributions; N samples; Planck radiation; RFI mitigation; double detector senses; microwave radiometry; process mean; radio-frequency interference; random process; sample variance estimator; statistical distribution; statistical variance; two-scale estimators; Approximation methods; Detectors; Interference; Microwave measurements; Microwave radiometry; Microwave theory and techniques; Noise; Electromagnetic interference; microwave radiometry; passive microwave remote sensing; statistical analysis;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2012.2219849
  • Filename
    6353137