RTSS:

Path: Common/Estimation

--------------------------------------------------------------------------
   Rauch-Tung-Striebel smoothing
   This assumes a discrete model of the form:

   x[k] = a[k-1]x[k-1] + b[k-1]u[k-1]
   y[k] = h[k]x[k]

   You pass all of the filter matrices that were already generated by
   a Kalman Filter.

   Type RTSS for a demo of a double integrator system.

   Since version 11.
--------------------------------------------------------------------------
   Form:
   [mS, pS] = RTSS( mP, pP, m, p, a )
--------------------------------------------------------------------------

   ------
   Inputs
   ------
   mP            (n,:)    Mean vector from KF prediction step
   pP            (n,n,:)  Covariance matrices from KF prediction step
   m             (n,:)    Mean vector from KF
   p             (n,n,:)  Covariance matrices from KF
   a             (n,n,:)  State transition matrices

   -------
   Outputs
   -------
   mS            (n,1)    Smoothed mean vector
   pS            (n,n)    Smoothed covariance matrix

--------------------------------------------------------------------------

Children:

Common: Estimation/KFPredict
Common: Estimation/KFUpdate
Common: Graphics/Plot2D
Common: Graphics/TimeLabl

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