NDLI: A statistical model of ionospheric signals in low-frequency SAR data

Content Provider	IEEE Xplore Digital Library
Author	Meyer, F.J. Watkins, B.
Copyright Year	2011
Description	Author affiliation: Geophysical Institute, University of Alaska Fairbanks, 903 Koyukuk Dr., Fairbanks, 99775, U.S.A. (Meyer, F.J.; Watkins, B.)
Abstract	This paper focuses on deriving a realistic statistical model for ionospheric effects in low-frequency Synthetic Aperture Radar (SAR) data. The approach used to develop this statistical model is based on the assumption that, for a certain range of scales, ionospheric plasma turbulence can be considered a scale-invariant process that can be described by power-law functions or fractal statistics. Based on the parameters of a power law model, covariance functions and ionospheric variance-covariance matrices are derived. An ionospheric phase statistics simulator (IP-STATS) is presented that is capable of calculating a variety of statistical descriptors and is able to predict representative ionospheric phase screens. To demonstrate its functionality and performance, the IP-STATS system is used to derive statistical models for a 10 year time series of L-band SAR data over the area of Alaska. The developed theory has potential applications in statistical modeling of SAR data, sensitivity analysis of spaceborne SAR systems, and signal simulation. IP-STATS may also be a useful tool in mission design especially in selecting favorable system center frequencies and orbit parameters.
Starting Page	1493
Ending Page	1496
File Size	555097
Page Count	4
File Format	PDF
ISBN	9781457710032
ISSN	21537003
e-ISBN	9781457710056
DOI	10.1109/IGARSS.2011.6049350
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data models Fractals Analytical models Mathematical model Covariance matrix Extraterrestrial measurements Indexes InSAR Ionosphere Statistics Power Spectra Covariance Functions Error Modeling SAR
Content Type	Text
Resource Type	Article

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