Computational Experience With The Generalized Kalman Filter For Dynamic Heave Compensation

Abstract

We treat the generalized Kalman Filter (GKF) approach to analyze heave dynamics data more effectively. An optimum solution that simultaneously accounts for the accuracy of the estimates and stability (lateral continuity) is achieved. Conventional Kalman Filters (KF) have been used in source heave compensation. One of the roblems continuity, since each trace is analyzed separately (single channel o eration). The approach establishes a trade off cost related to the lateral discontinuity of the estimates. By assigning pro er weights for accuracy and stability (WA and U’S) in the oRjective function the desired balance between accuracy and stability is achieved. Computational results are offered to illustrate the trade-offs involved. associatedwithKFis the difficulties inmaintaining t Tl elateral between t K e cost associated with estimation error and the