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srkf — square root Kalman filter
[x1,p1]=srkf(y,x0,p0,f,h,q,r)
| f, h | : current system matrices |
| q, r | : covariance matrices of dynamics and observation noise |
| x0, p0 | : state estimate and error variance at t=0 based on data up to t=-1 |
| y | : current observation Output from the function is |
| x1, p1 | : updated estimate and error covariance at t=1 based on data up to t=0 |
square root Kalman filter algorithm
C. B.
| << srfaur | sskf >> |