Attenuation and backscatter from a derived two-dimensional duststorm model

Fundamentals of attenuation and radar backscatter through duststorms are reviewed. A duststorm is modeled as circularly symmetric having a visibility with a minimum at its center (e.g., maximum mass loading) and which exponentially increases radially to a fixed maximum visibility threshold level (mi...

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Bibliographic Details
Published inIEEE transactions on antennas and propagation Vol. 49; no. 12; pp. 1703 - 1711
Main Author Goldhirsh, J.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.12.2001
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Fundamentals of attenuation and radar backscatter through duststorms are reviewed. A duststorm is modeled as circularly symmetric having a visibility with a minimum at its center (e.g., maximum mass loading) and which exponentially increases radially to a fixed maximum visibility threshold level (minimum mass loading). This model enables the convenient calculation of the two dimensional (2-D) structure of radar backscatter and path attenuation. As an example, the parameters of the exponential function describing the visibility distribution for a particular duststorm was derived using measurements made in the Sudan by other investigators operating a 10.5 GHz, 25 km link. A comparison of the calculated and measured attenuation time-series showed relatively close agreement. Both attenuation levels and backscatter levels due to even intense duststorms are expected to be relatively small for frequencies up to 10 GHz. For example, the peak attenuation for the duststorm that contained visibilities smaller than 2 m was less than 6.5 dB. Modeled backscatter due to this duststorm gave levels smaller than that obtained by an equivalent rainrate of 0.6 mm/h. Although the calculations were obtained for X-band, they may be extended to higher frequencies. Frequency scaling at 37 GHz, for example, showed a peak equivalent path attenuation level of at least 26.6 and 48 dB under varying assumptions.
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ISSN:0018-926X
1558-2221
DOI:10.1109/8.982449