Information augmentation of passive tracking for autonomous underwater vehicles

The problem of localizing moving targets using platform-based passive-acoustic sensing that may be available for small autonomous underwater vehicles is considered. An approach to maintaining the robust tracking performance, based on augmenting the nominal tracking function by nonbearing types of information extracted synergistically from knowledge-based data such as motion capabilities of different classes of targets and constraints of the operating environment, and from data gathered by onboard sensing/communication resources, is introduced. The implementation of approaches to augmenting the tracking function that help maintain robust tracking performance in the face of degraded bearing accuracy is described and results of their application are presented. Augmentation based on constraints on the relative platform-target motion, such as on the maximum speed capability of the target, the relative range etc., is discussed in detail