The generalized Kalman filter approach to adaptive underwater target tracking

The generalized Kalman filtering (GKF) method is applied to underwater target tracking. The proposed GKF is based on the formulation developed by J.C. Lagarias and F. Aminzadeh (1983) establishing a tradeoff between the cost associated with estimation error and the cost related to the lateral discontinuity of the estimates. By assigning proper weights for accuracy and stability in the objective function, the desired balance between accuracy of estimates and lateral continuity is achieved. Computational results illustrate the performance of the technique. Conclusions as to the effects of the accuracy and stability weights are drawn.>