Main Content

landreflectivity

Reflectivity of land surface

Since R2021a

collapse all in page

    Syntax

    nrcs = landreflectivity(landtype,ang)
    nrcs = landreflectivity(landtype,ang,freq)
    nrcs = landreflectivity(___,Model = model)
    nrcs = landreflectivity(___,Polarization = pol)
    nrca = landreflectivity(___,SurfaceHeightStandardDeviation = hgtsd)
    [nrcs,hgtsd,beta0,vegtype] = landreflectivity(___)

    Description

    nrcs = landreflectivity(landtype,ang) returns the surface radar reflectivity nrcs for the land type landtype at the grazing angle ang. Radar reflectivity is also called the normalized radar cross section (NRCS). This syntax assumes that the radar operates at 10 GHz and also assumes that the land model is the Barton reflectivity model. For a table of land models and land types, see Land Reflectivity Models and Land Types.

    example

    nrcs = landreflectivity(landtype,ang,freq) also specifies the transmitted frequency of the radar.

    nrcs = landreflectivity(___,Model = model) also specifies the reflectivity model.

    nrcs = landreflectivity(___,Polarization = pol) also specifies the polarization pol of the transmitted wave. To use this syntax, set the model argument to 'UlabyDobson'.

    nrca = landreflectivity(___,SurfaceHeightStandardDeviation = hgtsd) specifies the scalar standard deviation of the surface height hgtsd. To use this syntax, set the model argument to 'GIT'.

    [nrcs,hgtsd,beta0,vegtype] = landreflectivity(___) returns

    • hgtsd — the standard deviation of the surface height.

    • beta0 — the slope of the land type.

    • vegtype — the vegetation type.

    To enable this syntax, set the model argument to 'Barton'.

    Examples

    collapse all

    Open Live Script

    Calculate NRCS, surface height standard deviation, land slope, and vegetation type. Specify an urban land type and a grazing angle of 20 degrees.

    graz = 20;
[nrcs,hgtsd,beta0,vegtype] = landreflectivity("Urban",graz)
    nrcs = 
0.1082

    hgtsd = 
10

    beta0 = 
5.7296

    vegtype = 
'None'

    Input Arguments

    collapse all

    Surface land type, specified as a character array or string. The land type depends on the value of the model. For the acceptable land types for different models, see the table Land Models and Land Types.

    Grazing or depression angle of a surface relative to the radar, specified as a scalar or an M-length row vector of nonnegative values. When the land model is set to 'Billingsley', the angle is interpreted as a depression angle between –90° and 90°. For all other models, the angle is interpreted as a grazing angle ranging from 0° to 90°. Units are in degrees.

    Transmitted frequencies, specified as a positive scalar or R-length vector of positive values. Units are in Hz.

    Example: freq = 70e9

    Land reflectivity model, specified as a string or char. See the Land Models and Land Types table for all acceptable land reflectivity models.

    Polarization of reflectivity model, specified as 'H' for horizontal polarization, 'V' for vertical polarization, or 'HV' which indicates horizontal transmit with vertical receive.

    Dependencies

    To enable this argument, set the model argument to 'UlabyDobson'.

    Data Types: char | string

    Standard deviation of the surface height, specified as a scalar. Units are in meters.

    Dependencies

    To enable this argument, set the model argument to 'GIT'.

    Output Arguments

    collapse all

    Normalized surface reflectivity, returned as a real-valued M-by-R matrix. M is the length of the grazing angle vector graz or, for land surfaces, the depression angle vector. R is the length of the frequency vector freq. nrcs is dimensionless but often expressed as m²/m². Normalized reflectivity is also called normalized radar cross section (NRCS).

    Standard deviation of the surface height, returned as a scalar. Units are in meters.

    Dependencies

    To enable this argument, set the model argument to 'Barton'.

    Slope of the land type β0, returned as a scalar. Note that β0 is 1.4 times the RMS surface slope. Units are in degrees.

    Dependencies

    To enable this argument, set the model argument to 'Barton'.

    Vegetation type, returned a character array or string. The vegetation type depends on the land type.

    Land TypeVegetation Type

    Rugged Mountains

    Trees (dense)

    Mountains

    Trees (dense)

    Woods

    Trees (dense)

    Wooded Hills

    Trees (dense)

    Rolling Hills

    Brush (dense)

    Farm

    Grass (thin)

    Desert

    Grass (thin)

    Flatland

    Grass (thin)

    Metropolitan

    None

    Urban

    None

    Smooth

    None

    Dependencies

    To enable this argument, set the model argument to 'Barton'.

    Limitations

    This function assumes a Gaussian clutter model and that the reflectivity of land clutter is mostly independent of wavelength. The Gaussian model may fail to simulate the effects of some natural and most man-made structures, which are generally modeled separately as discrete clutter.

    More About

    collapse all

    Land Models and Land Types

    ModelLand TypeRange of Validity

    'Barton' – Constant-gamma mathematical model generally applicable over medium grazing angles. 'Barton' is the default model. See [1][2], and [3].

    'RuggedMountains'

    'Mountains'

    'Metropolitan'

    'Urban'

    'WoodedHills'

    'RollingHills'

    'Woods'

    'Farm'

    'Desert'

    'Flatland' (default for model)

    'Smooth'

    • Grazing angle 20 – 60 degrees

    • Frequency 1 – 10 GHz

    'APL' – This model also known as the ADSAM model. Low-fidelity constant-gamma mathematical model that includes specular scattering. See [4].

    'Urban'

    'HighRelief'

    'LowRelief' (default for model)

    • Grazing angle 0 – 90 degrees

    • Frequency 1 – 100 GHz

    'Billingesley' – High-validity empirical model generally applicable for low depression angles less than 2 degrees. See [5].

    'LowReliefRural' (default for model)

    'LowReliefForest'

    'Farm'

    'Desert'

    'Marsh'

    'Grassland'

    'HighReliefRural'

    'HighReliefForest'

    'Mountains'

    'Urban'

    'LowReliefUrban'

    • Depression angle -0.75 – 2 degrees

    • Frequency – VHF (0.030 – 0.3), UHF (0.3 – 1), L (1 -- 2), S (2 - 4), X (8 - 12) GHz

    'GIT' – Georgia Institute of Technology semi-empirical model takes into account terrain roughness. Generally applicable for medium grazing angles. See [6].

    'Soil' (default for Model)

    'Grass'

    'TallGrass'

    'Trees'

    'Urban'

    • Grazing angle 20 – 65 degrees

    • Frequency 3 – 15 GHz

    'Morchin' – Mathematical model generally applicable for high grazing angles for frequencies from UHF to C-band. See [7].

    'Desert'

    'Farm' (default for Model)

    'Woods'

    'Mountains'

    • Grazing angle 70 – 90 degrees

    • Frequencies UHF (0.3 – 1) L (1 – 2) S (2 – 4) C (4 – 8)

    'Nathanson' – Applicable up to Ka band for low grazing angle surface radars and medium grazing angle airborne radars for low mountains, farmland, and wooded areas. See [3].

    'Desert'

    'Farm' (default for Model)

    'Woods'

    'Jungle'

    'RollingHills'

    'Urban'

    • Grazing angle 0 – 60 degrees

    • Frequency L (1 – 2). S ( 2 – 4), C (4 – 8), X (8 --12), Ku (12 --18), Ka (32 -- 36) GHz

    'UlabyDobson' – High-validity semi-empirical model for low to medium grazing angles covering L-band to Ku, taking into account polarization. See [8].

    'Soil' (default for Model)

    'Grass'

    'Shrubs'

    'ShortVegetation'

    • Grazing angle 0 – 60 degrees

    • Frequency L (1 – 2), S ( 2 – 4), C (4 – 8), X (8 --12), Ku (12 --18) GHz

    References

    [1] Barton, David Knox. Radar Equations for Modern Radar. Artech House, 2013.

    [2] Long, Maurice W. Radar Reflectivity of Land and Sea. 3rd ed, Artech House, 2001.

    [3] Nathanson, Fred E., et al. Radar Design Principles: Signal Processing and the Environment. 2. ed., Repr, Scitech Publ, 2004.

    [4] 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.

    [5] Billingsley, J. Barrie. Low-Angle Radar Land Clutter: Measurements and Empirical Models. William Andrew Pub. : SciTech Pub. ; Institution of Electrical Engineers, 2002.

    [6] Richards, M. A., et al., editors. Principles of Modern Radar. SciTech Pub, 2010.

    [7] Morchin, Fred E., J. Patrick Reilly, and Marvin Cohen. Radar Design Principles: Signal Processing and the Environment. 2nd ed. New York: McGraw-Hill, 1991.

    [8] Ulaby, Fawwaz T., and M. Craig Dobson. Handbook of Radar Scattering Statistics for Terrain

    Extended Capabilities

    C/C++ Code Generation
    Generate C and C++ code using MATLAB® Coder™.

    Version History

    Introduced in R2021a

    See Also

    | | | | | |