Normalized sea surface reflectivity
returns the normalized sea surface reflectivity
nrcs = seareflectivity(
nrcs for the sea state
scale at the grazing angle
graz with the
freq. In this syntax, sea surface reflectivity is
calculated using the NRL Sea Clutter Model by Gregers-Hansen and Mittal. The reflectivity is
also called the normalized radar cross section (NRCS) and denoted
hgtsd— Standard deviation of the surface height for the specified sea state number.
beta0— Slope of the sea type.
beta0is 1.4 times the root mean square (RMS) surface slope. The surface σ0 value for sea clutter reflectivity is computed based on the NRL Sea Clutter Model by Gregers-Hansen and Mittal.
windvelocity— Wind velocity.
NRCS of Sea Clutter Patch
Calculate the NRCS of a sea clutter patch. Assume that the patch is the sea with sea state number equal to
2 and the radar system operates at a frequency of
30 GHz. Also assume the grazing angle is
scale = 2; graz = 10; freq = 30e9;
Calculate the normalized NRCS for the sea clutter patch.
nrcs = seareflectivity(scale,graz,freq)
nrcs = 2.1555e-04
You can use the normalized RCS to calculate the total clutter patch RCS.
Polarized Sea Reflectivity
Calculate and plot the horizontal and vertical reflectivities from the GIT model. The radar operates at an L-band frequency of 1.5 GHz at grazing angles from 0.1 to 10 degrees. Assume sea state 3.
seastate = 3; graz = 0.1:0.2:10; freq = 1.5e9; model = 'GIT';
Compute the horizontal and vertical polarized reflectivities.
reflh = seareflectivity(seastate,graz,freq, ... Model = model,Polarization = 'H'); reflv = seareflectivity(seastate,graz,freq, ... Model = model,Polarization = 'V');
Plot the reflectivities as a function of grazing angle.
plot(graz,pow2db(reflh)) hold on grid on plot(graz,pow2db(reflv)) legend('H','V','Location','Best') xlabel('Grazing Angle (deg)') ylabel('NRCS (dB)') title('GIT: NRCS at 1.5 GHz')
scale — Sea state or wind scale
If you set
scale is interpreted as the sea
state, specified as a nonnegative scalar between [0,8]. If you set
scale is interpreted as the
Beaufort wind scale, specified as a positive scalar between [1,9].
The interpretation of the
scale argument depends on the value
graz — Grazing angle
nonnegative scalar | N-length vector of grazing values
Grazing angle, specified as a nonnegative scalar or an N-length row
vector of nonnegative values. This argument specifies the grazing angles of the clutter
patch relative to the radar. Units are in degrees. See
freq — Transmitted frequencies
R-length vector of positive values
Transmitted frequencies, specified as a positive scalar or R-length vector of positive values. Units are in Hz.
freq = 70e9
pol — Polarization of transmitted wave
'H' (default) |
Polarization of transmitted wave, specified as
'H' for horizontal
'V' for vertical polarization.
scaletype — Scale type
'SeaState' (default) |
Scale type, specified as either:
'SeaState'— The function uses the Sea State model. When you specify this option, the
scaleinput scale must be a nonnegative scalar between [0,8].
'WindScale'— The function uses the Beaufort Wind Scale model. When you specify this option, the
scaleinput scale must be a positive scalars between [1,9].
model — Sea reflectivity model
'NRL' (default) |
Sea reflectivity model, specified as
'TSC'. The table Sea Reflectivity Models summarizes the sea
surface models available in the radar simulation and their domains of
lookang — Radar look angle
0 (default) | nonnegative scalar |
Radar look angle, specified as a nonnegative scalar between 0° and 180° or as:
Radar look angle is zero when looking upwind.
To enable this argument, set the model name to
nrcs — Normalized surface reflectivity
real-valued Q-by-R matrix | real-valued 2-by-2-by-Q-by-R array
Normalized surface reflectivity , returned as a real-valued
Q-by-R matrix or a real-valued
2-by-2-Q-by-R array. Q is
the length of the grazing angle
graz or, for land surfaces only,
depression angle. R is the length of the frequency vector
nrcs is dimensionless but often
expressed as m²/m². Normalized reflectivity is also called normalized radar cross
For the non-polarimetric reflectivity case,
nrcsis returned as a real-valued Q-by-R matrix.
For the polarimetric reflectivity case,
nrcsis returned as a real-valued 2-b-2-byQ-by-R array. For each value of Q and R,
NRCSforms a polarimetric normalized radar cross-section (NRCS) reflectivity matrix s of the form
where SHV and SVH are the cross-polarization components specified by the
ReflectivityVHproperties. The σ0HH and σ0VV components are derived from the specified model as set by the
The returned normalized reflectivity for cross-polarization components
calculated using nearest neighbor interpolation at a given grazing angle and frequency.
To avoid interpolation errors, the normalized reflectivity values in the
properties should cover grazing angles from 0–90 degrees and all expected
To enable the polarimetric reflectivity, set the
hgtsd — Standard deviation of surface height
Standard deviation of the surface height, returned as a scalar. The model for height deviation, surface slope, and wind velocity is based on a model by Barton. Units are in meters.
beta0 — Slope of the sea type
Slope of the sea type β0, returned as a scalar. The model for height deviation, surface slope, and wind velocity is based on a model by Barton. Units are in degrees.
windvelocity — Wind velocity
Wind velocity, returned as a scalar. The model for the height deviation, surface slope, and wind velocity is based on a model by Barton. Units are in meters per second.
Sea Reflectivity Models
|Model||Type||Grazing Angles||Frequency Range||Sea State|
|Empirical model||0.1° – 60°||0.5 – 35 GHz||0 – 6|
|Semi-empirical||0.1 – 10||1 – 100||1 – 6|
|Semi-empirical||0.1 – 10||1 – 100||1 – 6|
|Semi-empirical||0.1 – 30||0.5 – 35||0 – 5|
|Empirical||30 – 60||X (8 – 12) Ka (26.5 – 40)||1 – 6|
|Empirical||0.1 – 60||UHF (0.3 – 1), L (1 – 2), S(2 – 4), C(4 – 8), X(8 – 12), Ku(12 – 18), Ka(32 – 36)||0 – 6|
|Mathematical||< 10||9 – 10||1 – 6|
|Empirical||0.2 – 10||X (8 – 12)||0 – 7|
|Empirical||0.1 – 90||0.5 – 35||0 – 5|
 Gregers-Hansen, V. and Mittal, R. "An Improved Empirical Model for Radar Sea Clutter Reflectivity." NRL/MR/5310-12-9346, Apr. 27, 2012.
 Barton, David Knox. Radar Equations for Modern Radar. Artech House, 2013.
 Reilly, J. P., R. L. McDonald, and G. D. Dockery. "RF-Environment Models for the ADSAM Program." Report No. A1A97U-070, Laurel, MD: Johns Hopkins University Applied Physics Laboratory, August 22, 1997.
 Ward, Keith D., Simon Watts, and Robert J. A. Tough. Sea Clutter: Scattering, the K-Distribution and Radar Performance. IET Radar, Sonar, Navigation and Avionics Series 20. London: Institution of Engineering and Technology, 2006.
 Antipov, Irina. "Simulation of Sea Clutter Returns." Department of Defence, June 1998.
 Masuko, Harunobu, Ken'ichi Okamoto, Masanobu Shimada, and Shuntaro Niwa. "Measurement of Microwave Backscattering Signatures of the Ocean Surface Using X Band and K a Band Airborne Scatterometers." Journal of Geophysical Research 91, no. C11 (1986): 13065. https://doi.org/10.1029/JC091iC11p13065.
 Nathanson, Fred E., et al. Radar Design Principles: Signal Processing and the Environment. 2. ed., Repr, Scitech Publ, 2004.
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Introduced in R2021a