Date of Award

5-2012

Degree Name

MS in Computer Science

Department

Computer Science

Advisor

Christopher M. Clark

Abstract

This thesis presents the integration of an acoustic tracking system within an autonomous underwater AUV (AUV) to enable real-time tracking of sharks tagged with artificial acoustic sources. The tracking system consists of two hydrophones and a receiver unit that outputs a measurement of the relative angle to the tagged shark. Since only two hydrophones are used, the sign of the relative angle measurement is unknown. To overcome this ambiguity, a particle filter algorithm was developed to estimate the position of the acoustic source. When combined with an active control system that drives vehicle to obtain different orientations with respect to the acoustic source, real-time autonomous localization, tracking, and following of a tagged shark is shown to be possible. Four types of ocean experiments were used to validate the system including: 1) AUV tracking of a stationary tag, 2) AUV tracking of a tagged kayak, 3) AUV tracking of a tagged AUV, and 4) AUV tracking of a tagged shark. These experiments were analyzed with respect to the localization error, associated error variance, and distance between the AUV and the tag. The final shark tracking experiments took place in SeaPlane Lagoon, Los Angeles, CA, where the AUV was able to autonomously track and follow a tagged Leopard Shark for several hours.

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