|dc.description.abstract||This thesis addresses the performance of two underwater localization estimator. The localization system under consideration is passive and employs three submerged omnidirectional sensors in a deep multipath ocean environment. The performance measure used is the variance of the localization estimator.
First, localization variance expressions are developed for a three parameter estimator. In this scenario, only the three coordinates of source location are estimated. These variance expressions are derived under conditions where, 1) only the ocean noise is considered; 2) only the sensor perturbations are considered; and 3) the combined effect due to 1) and 2) are considered. The theoretical expression are corroborated with Monte-Carlo simulation.
Second, the localization variance expressions are developed for a five parameter estimator. In this scenario, the two vertical positions of sensors are estimated in addition to the coordinates of source location. The estimated sensor positions are used in the localization. The expressions are also developed under the three same situations mentioned above. These expressions are also. corroborated with Monte Carlo simulation.
The results of the theoretical analysis show that if the variance of sensor perturbations is small, the three parameter estimator is a better choice. If the variances of the perturbations are large, the localization performance of the five parameter estimator is better than the performance in three parameter estimator for surface ranges of more than a few kilometers. Furthermore, the performance of the five parameter
estimator improves increasingly relative to the performance of the three parameter estimator as the variance of the sensor perturbations increases.||en_US