Comparison of Kalman and finite memory filtering for gun fire control applications

A finite memory filter is developed for gun fire control and compared to a Kalman filter. As opposed to the Kalman filter, the finite memory filter does not require a priori information concerning measurement or target noise statistics. In addition, the finite memory filter was implemented using a new recursive algorithm which dramatically reduces its computational burden. It is shown for gun fire control applications, the Kalman filter requires at least an order of magnitude more computation to achieve the same performance as a finite memory filter.