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rocinterp

ROC curve interpolation

    Description

    example

    ipd = rocinterp(snr,pd,snrq,'snr-pd') returns the probability of detection (Pd) computed by interpolating a Pd vs. signal-to-noise ratio (SNR) receiver operating characteristic (ROC) curve. If pd is a matrix, the function interpolates each column independently. In this and the next syntax, rocinterp performs linear interpolation after transforming the Pd-axis of the ROC curve using the normal probability scale.

    example

    isnr = rocinterp(pd,snr,pdq,'pd-snr') returns the SNR computed by interpolating a Pd vs. SNR ROC curve. If snr is a matrix, the function interpolates each column independently.

    example

    ipd = rocinterp(pfa,pd,pfaq,'pfa-pd') returns the Pd computed by interpolating a Pd vs. probability of false alarm (Pfa) ROC curve. If pd is a matrix, the function interpolates each column independently. In this and the next syntax, rocinterp performs linear interpolation after transforming both axes of the ROC curve using a logarithmic scale.

    example

    ipfa = rocinterp(pd,pfa,pdq,'pd-pfa') returns the Pfa computed by interpolating a Pd vs. Pfa ROC curve. If pfa is a matrix, the function interpolates each column independently.

    Examples

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    Compute the probability of detection (Pd) for a Swerling 1 case target given a set of signal-to-noise ratio (SNR) and probability of false alarm values. Express the SNR values in decibels.

    SNR = [13.5 14.5];
    pfa = [1e-9 1e-6 1e-3];

    Compute the Pd vs. SNR ROC curves and interpolate them at the SNR values of interest.

    [pd,snr] = rocpfa(pfa,'SignalType','Swerling1');
    
    ipd = rocinterp(snr,pd,SNR,'snr-pd');

    Plot the ROC curves and overlay the interpolated values.

    rocpfa(pfa,'SignalType','Swerling1')
    hold on
    q = plot(SNR,ipd,'*');
    hold off
    legend(q,append("P_{fa} = ",string(pfa),", int."),'Location','northwest')

    Figure contains an axes object. The axes object with title Swerling1 Receiver Operating Characteristic (ROC) Curves contains 9 objects of type line, text. These objects represent P_{fa} = 1e-09, int., P_{fa} = 1e-06, int., P_{fa} = 0.001, int..

    Input Arguments

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    Signal-to-noise ratio in decibels (dB), specified as a vector or matrix. If snr is a vector, its values must be unique. If snr is a matrix, then each of its columns must contain unique values.

    Data Types: double

    Signal-to-noise ratio query points, specified as a vector. All values of snrq must be expressed in dB.

    Data Types: double

    Probability of detection, specified as a vector or matrix. All values of pd must be between 0 and 1. If pd is a vector, its values must be unique. If pd is a matrix, then each of its columns must contain unique values.

    Data Types: double

    Probability of detection query points, specified as a vector. All values of pdq must be between 0 and 1.

    Data Types: double

    Probability of false alarm, specified as a vector or matrix. All values of pfa must be between 0 and 1. If pfa is a vector, its values must be unique. If pfa is a matrix, then each of its columns must contain unique values.

    Data Types: double

    Probability of false alarm query points, specified as a vector. All values of pfaq must be between 0 and 1.

    Data Types: double

    Output Arguments

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    Interpolated probability of detection, returned as a vector or matrix.

    Interpolated signal-to-noise ratio, returned as a vector or matrix.

    Interpolated probability of false alarm, returned as a vector or matrix.

    Extended Capabilities

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

    Introduced in R2021a