We consider the challenge of prioritizing among a set of simultaneous goals in an intelligent active sonar system. The cognitive (or intelligent) sonar system we propose is one that is capable of making decisions and tuning parameters to best achieve a set of possibly competing goals. Integrating intelligence in the sonar system reduces the burden on system operators and has the potential to greatly improve how quickly and how well systems can meet surveillance and tracking goals. We propose applying the goal-driven autonomy (GDA) architecture to intelligent active sonar, and in this paper we focus on the issue of assigning priority to system goals when multiple goals are simultaneously active. The goals are to track each of three targets simultaneously, and the decision to be made is which sector of the surveillance space to illuminate at each ping interval. We propose a metric for determining priority that incorporates both uncertainty about target state and the level of risk posed by the target. Simulation results indicate that the proposed goal management takes actions that decrease uncertainty about higher risk targets and has the potential to prioritize goals based on intelligence gathered from multiple system sources.