Application of Kalman filter and input estimation for underwater target tracking

The feasibility of the extended Kalman filter using range and bearing measurements is explored for on-sea water applications. The input estimation technique used for in-air applications is tried and extended to on-sea water applications. The algorithm estimates target motion parameters and detects target maneuver using chi-square distributed random sequence residual. Upon detection of target maneuver, this algorithm corrects the velocity and position components using acceleration components, which are calculated using input estimation technique. Finally, the performance of this algorithm is evaluated in Monte-Carlo simulation.