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Multiple scattering effects on communication and imaging through random media

Communication through turbulence and particulate matters such as rain are seriously affected by multiple scattering. We present a study on multiple-input-multiple-output system in random medium and its channel capacity making use of the stochastic Green’s functions and the mutual coherence function...

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Bibliographic Details
Published in:The Journal of the Acoustical Society of America 2009-10, Vol.126 (4_Supplement), p.2272-2272
Main Authors: Ishimaru, Akira, Jaruwatanadilok, Sermsak, Kuga, Yasuo
Format: Article
Language:English
Online Access:Get full text
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Summary:Communication through turbulence and particulate matters such as rain are seriously affected by multiple scattering. We present a study on multiple-input-multiple-output system in random medium and its channel capacity making use of the stochastic Green’s functions and the mutual coherence function (MCF). The channel matrix and the eigenvalues are given explicitly in terms of the medium characteristics, and the channel capacity is given in terms of signal-to-noise ratios, eigenvalues, and the antenna gain characteristics. MCF is given in terms of the power spectrum for turbulence and the optical depth, phase function, and albedo for particulate matters. Next, we consider imaging through random medium such as biological media. We present several space-time array signal processing imaging techniques which include time-reverse imaging, time-reverse multiple signal classification, Capon minimum variance, modified beam former, and SAR. We discuss the advantages and the disadvantages of these techniques with numerical examples. The effects of array sizes, Fresnel size, bandwidth, the distance, and the medium characteristics on the transverse and longitudinal resolutions are clarified. This study is aimed at combining the propagation and scattering and the array signal processing for communication and imaging in a random complex environment such as turbulence and biological media.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.3249302