model

SLAM.Inertial.SchmidtReferencePrediction

Public declarations

Explicit source declarations; dimensions, modifications and defaults are shown as written, without evaluation.

Role	Name	Type	Dimensions / attributes / default
constant	`currentDimension`	`Integer`	`= 15`
constant	`referenceDimension`	`Integer`	`= 6`
input	`covariance`	`Real`	`[currentDimension,currentDimension]`
input	`crossCovariance`	`Real`	`[currentDimension,referenceDimension]`
input	`referenceCovariance`	`Real`	`[referenceDimension,referenceDimension]`
input	`transition`	`Real`	`[currentDimension,currentDimension] = identity(currentDimension)`
input	`processCovariance`	`Real`	`[currentDimension,currentDimension] = zeros(currentDimension,currentDimension)`
input	`referenceAvailable`	`Real`	`= 0.0`
input	`predictionEnabled`	`Real`	`= 1.0`
output	`accepted`	`Real`
output	`nextCovariance`	`Real`	`[currentDimension,currentDimension]`
output	`nextCrossCovariance`	`Real`	`[currentDimension,referenceDimension]`
output	`nextReferenceCovariance`	`Real`	`[referenceDimension,referenceDimension]`

Modelica declarations and implementation

Show parameters, interfaces and source

Parameters, inputs, outputs, defaults and equations from the source file.

model SchmidtReferencePrediction
  import SchmidtPredictCovariance = SLAM.Inertial.SchmidtPredictCovariance;

  constant Integer currentDimension = 15;
  constant Integer referenceDimension = 6;
  input Real covariance[currentDimension,currentDimension];
  input Real crossCovariance[currentDimension,referenceDimension];
  input Real referenceCovariance[referenceDimension,referenceDimension];
  input Real transition[currentDimension,currentDimension] = identity(currentDimension);
  input Real processCovariance[currentDimension,currentDimension] = zeros(currentDimension,currentDimension);
  input Real referenceAvailable = 0.0;
  input Real predictionEnabled = 1.0;
  output Real accepted;
  output Real nextCovariance[currentDimension,currentDimension];
  output Real nextCrossCovariance[currentDimension,referenceDimension];
  output Real nextReferenceCovariance[referenceDimension,referenceDimension];
algorithm
  (accepted,nextCovariance,nextCrossCovariance,nextReferenceCovariance)
    := SchmidtPredictCovariance(covariance,crossCovariance,referenceCovariance,
      transition,processCovariance,referenceAvailable,predictionEnabled);
end SchmidtReferencePrediction;