Unscented Kalman Filter

Class implementing unscented Kalman filter.

This class implements the unscented Kalman filter algorithm. It accepts a model of the explicit discrete time-variant form:

   x(t+dt) = stateEqn(t,x(t),u(t),noise,dt)
      y(t) = outputEqn(t,x(t),u(t),noise)

where process and sensor noise are defined by covariance matrices Q and R.

State and output equations must be defined in a vectorized form, i.e., so that they can take several samples of state, input, output, and noise. Matrices must be formed such that the row represents the variable and the column the sample.

Methods

• initialize(UKF,t0,x0,u0) - Initialize filter given initial time, state, and inputs
• estimate(UKF,t,u,z) - Update the state and output estimates given new input and output data.
• getStateEstimate(UKF) - Return a state estimate structure with mean and covariance.

See also Kalman Filter, Extended Kalman Filter, Particle Filter.