AIAntenna

Create AI-model-based antenna to explore design space

Since R2023b

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    Description

    The AIAntenna object lets you use a pretrained AI-based model of a catalog antenna 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 includes two fixed read-only properties that apply to all supported catalog elements, along with additional element‑specific tunable or read‑only dynamic properties. See the individual catalog‑element documentation pages for details on these dynamic properties.

    Supported catalog-elements:

    Properties

    expand all

    This property is read-only.

    Antenna type from the supported antenna catalog elements, 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, AI-based antenna, platform, or shape
    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