ANALYSIS OF EXTENED KALMAN FILTER USING RANGE AND LINE OF SIGHT MEASUREMENT FOR UNDERSEA TARGET LOCALISATION

Abstract

The feasibility of the extended Kalman filter using range and bearing measurements is explored for underwater applications. The Input estimation technique, developed by Bar-Shalom and Fortmann for radar applications is implemented for sonar applications. Input estimation is used to estimate the target acceleration whenever the target makes a maneuver. The algorithm estimates target motion parameters and detects target maneuver using zero mean chi-square distributed random sequence residual. Upon detection of target maneuver, this algorithm corrects the velocity and position components using acceleration components. Finally, the performance of this algorithm is evaluated in Monte-Carlo simulations and results are shown for various typical geometries and found that this input estimation technique can be used for underwater applications.