This talk will present recent research on the use of information-theoretic approaches for managing the sensor network responsible for detecting, tracking, and cataloging space objects in support of space situational awareness. Specifically, we formulate the problem of tracking multiple spacecraft using a combination of ground- and spacebased sensors. The problem is formulated in a simplified two-dimensional setting to reduce computational complexity while retaining elements of the problem that pose theoretical or practical difficulties (such as the nonlinear inverse-square gravity dynamics). As a baseline approach for comparision purposes, a centralized Extended Kalman Filter (EKF) estimator is used to provide position and velocity estimates of all tracked objects. These estimates and their associated covariances are used to execute a closed-loop sensor tasking approach to determine which sensors will track which objects. A tasking approach from the literature is utilized as a baseline methodology and compared to an ad-hoc modification which may offer improved performance in certain situations. The paper concludes with a numerical example demonstrating the approaches as well as a summary of avenues for future research.