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Get copy of PHD filter

Since R2023a



filter = getPHDFilter(tracker) returns a copy of the probability hypothesis density (PHD) filter used in the tracker at the current time.


  • You must run the tracker object at least once before using this object function.

  • Changes applied to the returned filter do not affect the tracker object.


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Create a trackingSensorConfiguration object and create a trackerPHD object based on the configuration settings.

config = trackingSensorConfiguration(1,IsValidTime=true);
tracker = trackerPHD(SensorConfigurations=config);

Create a objectDetection object and update the tracker with the detection.

detection = objectDetection(0,[0 0 0],SensorIndex=1);

Get a copy of the PHD filter object used in the tracker.

filter = getPHDFilter(tracker)
filter = 
  ggiwphd with properties:

                         States: [6x1 double]
               StateCovariances: [6x6 double]
                  PositionIndex: [1 3 5]
             StateTransitionFcn: @constvel
     StateTransitionJacobianFcn: @constveljac
                   ProcessNoise: [3x3 double]
        HasAdditiveProcessNoise: 0

                         Shapes: 1
                          Rates: 1
         GammaForgettingFactors: 1.0300

               DegreesOfFreedom: 101
                  ScaleMatrices: [3x3 double]
              ExtentRotationFcn: @(x,dT)eye(3,class(x))
                  TemporalDecay: 100

                        Weights: 2.2204e-19
                         Labels: 0

                     Detections: {[1x1 objectDetection]}
                 MeasurementFcn: @cvmeas
         MeasurementJacobianFcn: @cvmeasjac
    HasAdditiveMeasurementNoise: 1

Input Arguments

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PHD tracker, specified as a trackerPHD object.

Output Arguments

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PHD filter, returned as a gmphd object or a ggiwphd object.

Extended Capabilities

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

Version History

Introduced in R2023a