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cfarloss

Loss due to constant false alarm rate (CFAR) adaptive processing

Since R2021a

    Description

    example

    LCFAR = cfarloss(PFA,NRC) computes approximated CFAR loss, LCFAR, in dB for the probability of false alarm, PFA, and number of reference cells, NRC, that you specify. The function calculates loss for the cell-averaging (CA) CFAR method and a square-law detector based on the Gregers-Hansen's universal CFAR loss curve.

    LCFAR = cfarloss(PFA,NRC,Name,Value) specifies additional options using name-value arguments. For example, LCFAR = cfarloss(1e-8,4:4:64,'Method','CA') computes approximate loss using the CA CFAR process.. You can specify multiple name-value arguments.

    Examples

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    Calculate the CFAR loss for an n-cell averaging and a square-law detector. Assume the numbers of reference cells from 4–64 and the probability of false alarm of 1e-8.

    PFA = 1e-8;
    NRC = 4:4:64;     
    LCFAR = cfarloss(PFA,NRC);

    Plot the resulting loss vs CFAR ratio. The CFAR ratio is calculated using the equation, X = -log10(PFA)/NRC.

    plot(-log10(PFA)./NRC,LCFAR)
    grid on;
    xlabel('CFAR Ratio = -log_{10}(PFA)/NRC');
    ylabel('CFAR Loss (dB)');
    title({'Universal Curve for CFAR Loss for',...
           'n-cell Averaging and Square-Law Detector'});

    Input Arguments

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    Probability of false alarm, specified as a positive scalar in the range [1e-15,1e-3] or as a length-K vector with each element in the range [1e-15,1e-3] .

    Number of reference cells used in CFAR processing, specified as a positive scalar or length-K vector.

    Name-Value Arguments

    Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

    Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

    Example: LCFAR = cfarloss(1e-8,4:4:64,'DetectorType','Log')

    Type of CFAR process, specified as a either 'CA' for cell-averaging process or 'GOCA' for greatest-of cell-averaging process.

    Example: 'Method','GOCA'

    Type of detector in use, specified as either 'SquareLaw', 'Linear', or 'Log'.

    Example: 'DetectorType','Linear'

    Output Arguments

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    CFAR loss, returned as a K-element vector in dB.

    Extended Capabilities

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

    Version History

    Introduced in R2021a