wuyou33 / matrix-fisher-gaussian

Distribution and filtering on SO(3) x Euclidean space

Matrix-Fisher-Gaussian

Distribution and filtering on SO(3) x Euclidean space

List of parameters

• angular velocity noise parameters

  • parameters.omegaNoise.randomWalk: random walk noise for angular velocity
  • parameters.omegaNoise.biasInstability: bias random walk noise for angular velocity

• measurement noise parameters

  • parameters.meaNoise
    • A 3-by-3 matrix if meaIsVec==false, representing the covariance for attitude uncertainty (GaussMea==true), or S for attitude uncertainty (GaussMea==false).
    • A nVecRef-by-1 vector if meaIsVec==true, representing the variance for isotropic vector measurement uncertainty (GaussMea==true), or kappa for unit vector uncertainty (GaussMea==false).

• other settings

  • parameters.setting.omegaLocal: true if angular velocity is measured in body-fixed frame; false if angular velocity is measured in inertial frame.
  • parameters.setting.GaussMea: true if the measurement noise is Gaussian; false if the measurement noise is matrix Fisher (meaIsVec==false) or von Mises Fisher (meaIsVec==true).
  • parameters.setting.meaIsVec: true if measurements are vectors; false if measurement is attitude.

• vector measurement settings

  • parameters.setting.vecRefInertial: true if reference vector is in inertial frame; false if reference vector is in body-fixed frame.
  • parameters.setting.nVecRef: number of reference vectors.
  • parameters.setting.vRef: reference vectors, a 3*nVecRef-by-1 vector.

• attitude measurement settings

  • parameters.setting.attMeaLocal: true if the noise is in the body-fixed frame; false if the noise is in inertial frame.

• initialization settings

  • parameters.initValue.Miu: initial bias, which is to be substracted.
  • parameters.initValue.U
  • parameters.initValue.V
  • parameters.initValue.xNoise: covariance for the initial bias
  • parameters.initValue.RNoise: covariance for initial attitude (GaussMea==true), or S for initial attitude (GaussMea==false).