Adaptive underwater target tracking via a generalized Kalman filter

An underwater target tracking scheme is presented. A model relating the target states to time delay and bearing measurements is reviewed. This provides linearized measurement models which are discussed. One of the problems associated with Kalman filters is difficulties in maintaining the lateral continuity of received data. This is due to the fact that in most published results each trace is analyzed separately (single-channel operation). Accounting for and utilizing spatial variations (as opposed to time variations) becomes just as significant as any type of time series analysis of individual traces. The proposed generalized Kalman filter 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 subjective function the desired balance between accuracy and stability is achieved