AIAntenna

Create AI model-based antenna object for design space exploration

Since R2023b

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    Description

    The AIAntenna object lets you utilize an AI-based model of an antenna catalog element for rapid characterization and design space exploration. Using AI-based antenna models over conventional full-wave solvers significantly reduces the simulation time required to fine-tune the antenna to meet your design goals.

    Creation

    You can create an AIAntenna object for the supported catalog elements by setting the ForAI name-value argument to true in the design function. The AIAntenna object has two fixed read-only properties common for all the supported catalog elements and other element specific tunable or read-only dynamic properties. See the individual catalog element pages for details on these dynamic properties.

    Supported catalog elements:

    Properties

    expand all

    This property is read-only.

    Antenna type from the antenna catalog, returned as a string.

    Example: "patchMicrostrip"

    Data Types: string

    This property is read-only.

    Initial design frequency used to create the AIAntenna, returned as a positive scalar in Hertz.

    Example: 1e9

    Data Types: double

    Object Functions

    bandwidthCalculate absolute bandwidth of AI-based antenna
    beamwidthCalculate Half-Power Beamwidth (HPBW) of AI-based antenna
    defaultTunableParametersGet default values of tunable properties
    exportAntennaExport tunable property values of AI-based antenna to equivalent catalog element
    peakRadiationCalculate maximum radiation points of AI-based antenna
    resonantFrequencyCalculate resonant frequency of AI-based antenna
    resetReset tunable property values to default
    showDisplay antenna, array structures, shapes, or platform
    tunableRangesFind upper and lower bounds of tunable properties

    Examples

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    This example uses:

    Open Live Script

    This example shows how to create an AI-based microstrip patch antenna operating at 1.67 GHz, and calculate its bandwidth and resonant frequency.

    Use the design function with the ForAI argument set to true to create an AI-based microstrip patch antenna operating at 1.67 GHz. To use the ForAI argument in the design function you need a license to the Statistics and Machine Learning Toolbox™.

    pAI = design(patchMicrostrip,1.67e9,ForAI=true)
    pAI = 
  AIAntenna with properties:

   Antenna Info
               AntennaType: 'patchMicrostrip'
    InitialDesignFrequency: 1.6700e+09

   Tunable Parameters
                    Length: 0.0862
                     Width: 0.1122
                    Height: 0.0018

Show read-only properties

    Explore the design space by changing its length and width with values within the tunable range of these properties. You can get the tunable range of a property by using tunableRanges function on the AI-based antenna object. 

    pAI.Length = 0.0855;
pAI.Width = 0.113;

    Calculate the absolute bandwidth of the antenna and its lower and upper bounds.

    [absBW,fL,fU,matchingStatus] = bandwidth(pAI)
    absBW = 
2.3422e+07

    fL = 
1.6679e+09

    fU = 
1.6913e+09

    matchingStatus = categorical
     Matched

    Calculate the resonant frequency of the antenna. 

    fR = resonantFrequency(pAI)
    fR = 
1.7016e+09

    Convert the AI-based microstrip patch antenna to a regular microstrip patch antenna.

    pm = exportAntenna(pAI)
    pm = 
  patchMicrostrip with properties:

               Length: 0.0855
                Width: 0.1130
               Height: 0.0018
            Substrate: [1×1 dielectric]
    GroundPlaneLength: 0.1795
     GroundPlaneWidth: 0.1795
    PatchCenterOffset: [0 0]
           FeedOffset: [0.0181 0]
            Conductor: [1×1 metal]
                 Tilt: 0
             TiltAxis: [1 0 0]
                 Load: [1×1 lumpedElement]

    References

    [1] Sivaramakrishnan, Sudarshan, Vishwanath Iyer, Tina Gao, and Giorgia Zucchelli. “A Systematic Application of AI Techniques to Antenna Design, Analysis, and Optimization.” In 2024 54th European Microwave Conference (EuMC), 972–75. Paris, France: IEEE, 2024. https://doi.org/10.23919/EuMC61614.2024.10732562.

    Version History

    Introduced in R2023b

    See Also

    Functions

    Topics