Reduced update Kalman filter: a two-dimensional recursive processor
John W. Woods, C.H. Radewan · University of North Texas Digital Library (University of North Texas) · 1976
The Kalman filtering method is extended to two-dimensions. The resulting computational load is found to be excessive. The reduced update Kalman filter is derived. It is shown to be optimum in that it minimizes the post update mean square error (mse) under the constraint of updating only the nearby previously processed neighbors. The resulting filter is a stable, nonsymmetric half-plane recursive filter. This method is proposed as a solution of the 2-D filter design problem for stochastic dynamical models.