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A Simple Model for Marine Radar Images of the Ocean Surface A Simple Model for Marine Radar Images of the Ocean Surface

A Simple Model for Marine Radar Images of the Ocean Surface - PowerPoint Presentation

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Uploaded On 2015-11-09

A Simple Model for Marine Radar Images of the Ocean Surface - PPT Presentation

David R Lyzenga David T Walker SRI International Inc Ann Arbor MI SOMaR3 Workshop July 1416 2015 Seattle WA Bragg Scattering According to the smallperturbation method eg Valenzuela 1978 the normalized radar cross section of the ocean surface can be written as ID: 188299

surface slope log shadowed slope surface shadowed log image signal regions function averaged bragg time radar model marine written

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Slide1

A Simple Model for Marine Radar Images of the Ocean Surface

David R. LyzengaDavid T. WalkerSRI International, Inc.Ann Arbor, MI

SOMaR-3 Workshop

July 14-16, 2015

Seattle, WASlide2

Bragg Scattering

According to the small-perturbation method (e.g. Valenzuela, 1978) the normalized radar cross section of the ocean surface can be written as where  is the local incidence angle,  is the azimuthal angle, k is the radar wavenumber, gpp( ) is the first-order Bragg scattering coefficient, kB = 2k sin

is the Bragg wavenumber, and S(k,) is the wave spectrumAt low grazing angles, and for horizontal polarization, this reduces to where , and where r is the radial component of the surface slope, h is the antenna height, and r is the range distance Slide3

Approximation of Log Function

Most marine navigational radars employ a logarithmic amplifier, and the video signal (or image intensity) can be written as I = a log(Pr /Pn +1) where Pr is the received power and Pn is the noise powerCoincidentally, the log function is closely approximated by the fourth root function, i.e. for 0 < Pr

/

P

n < 200Slide4

Log-Amplified Signal Model

Combining this approximation for the log function with the Bragg scattering model for low grazing angles, and including an r -3 falloff in the received power, we have the expression for the log-amplified video signal or image intensity, neglecting antenna gain variationsIf there were no wave shadowing, averaging this signal over time would yield the result since r  = 0Slide5

Wave Shadowing Effects

From simple geometric considerations, the mean surface slope within any geometrically shadowed region can be shown to be equal to –h/r (for r » h »  )The ensemble-averaged slope in partially shadowed regions can then be written as r  = f

s

rs  + (1 – fs)ri  = 0

where f

s is the shadowing fraction, rs 

= –h

/r is the mean slope in shadowed regions, and ri 

is the mean slope in illuminated (unshadowed) regionsThe average surface slope in

unshadowed regions is therefore ri

 =

(

h

/

r

)

f

s

/ (1

f

s

)The time-averaged signal in partially shadowed regions is thenSlide6

Comparisons With Marine Radar Data

Time-averaged X-band image intensities collected from FLIP during Hi-Res experiment (courtesy Eric Terrill, Scripps Institution)

Time-averaged X-band image intensities collected near Newport, Oregon (courtesy Merrick Haller, Oregon State University)Slide7

Surface Slope Estimation

Using the previously described model, the radial component of the surface slope can be estimated as where , is the image intensity and represents a suitable ensemble average (possibly a low-pass filtered version) of the image intensityThis relationship is assumed to be valid in unshadowed regions: within shadowed portions of the surface and , and this equation yields an estimated slope of – h / r, which is a valid estimate of the slope at the first shadowed point and of the mean slope within the shadowed region