ABSTRACT In passive underwater target tracking, the observer uses bearings-only measurements generated by radiation of the target. The measurements are always corrupted with noise, which creates an uncertainty zone around the target position. Unscented Kalman filter (UKF) is proved to be efficient nonlinear estimator to estimate the target motion parameters. It is of interest to know in many practical situations, regarding the convergence of the solution in terms of the reduction of the uncertainty zone within some specified limit. An effort is made to reduce and find the range uncertainty ellipse zone of the target using UKF covariance matrix in Monte Carlo simulation. Once the range uncertainty ellipse zone becomes less than a specified value, the solution is said to be converged. ABBREVIATIONS: RUEZ: Range Uncertainty Ellipse Zone; UKF: Unscented Kalman Filter; UT: Unscented Transformation; LHMA: Length of Half Major Axis
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