src/ukf.cpp
void UKF::Prediction(double delta_t) {

  // defining matrix for holding the augmented sigma points
  MatrixXd Xsig_aug = MatrixXd(n_aug_, n_sigma_);
  Xsig_aug.fill(0.0);

  // 1: generate sigma points
  GenerateSigmaPoints(Xsig_aug);

  // 2: predict sigma points
  PredictSigmaPoints(delta_t, Xsig_aug);

  // 3: predict mean and covariance
  PredictMeanAndCovariance();
}
/**
 * Predicts sigma points, the state, and the state covariance matrix.
 * @param {double} delta_t the change in time (in seconds) between the last
 * measurement and this one.
 */
Predicts sigma points, the state, and the state covariance matrix.
@param {double} delta_t the change in time (in seconds) between the last
measurement and this one.
Predicts sigma points the state and the state covariance matrix . @param { double } delta_t the change in time ( in seconds ) between the last measurement and this one .
void UKF::Prediction(double delta_t) {
  MatrixXd Xsig_aug = MatrixXd(n_aug_, n_sigma_);
  Xsig_aug.fill(0.0);
  GenerateSigmaPoints(Xsig_aug);
  PredictSigmaPoints(delta_t, Xsig_aug);
  PredictMeanAndCovariance();
}
void UKF :: Prediction ( double delta_t ) { MatrixXd Xsig_aug = MatrixXd ( n_aug_ , n_sigma_ ) ; Xsig_aug . fill ( 0.0 ) ; GenerateSigmaPoints ( Xsig_aug ) ; PredictSigmaPoints ( delta_t , Xsig_aug ) ; PredictMeanAndCovariance ( ) ; }
Predicts sigma points, the state, and the state covariance matrix.
Predicts sigma points the state and the state covariance matrix .
// defining matrix for holding the augmented sigma points // 1: generate sigma points // 2: predict sigma points // 3: predict mean and covariance