Underwater tracking of a maneuvering target using time delay measurements

Abstract The problem of estimating the relative position of an underwater maneuvering target is treated as an estimation problem when an unknown and time varying bias is present in the plant noise process. Pilot-initiated maneuvers are modeled as impulsive unknown inputs affecting the bias term at times unknown to the observer. A new algorithm, capable of efficiently handling the problem of state estimation with time varying unknown bias, is derived by using the Lainiotis multimodel partitioning theory coupled with conventional constant bias estimation algorithms. Simulation results show that the proposed algorithm performs very well under adverse operating conditions, such as high measurement noise, long target to observer range and large-scale target maneuvers.