srkf

square root Kalman filter

Calling Sequence

[x1,p1]=srkf(y,x0,p0,f,h,q,r)

Arguments

: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

:

Description

square root Kalman filter algorithm