Comparison of information theoretic divergences for sensor management

Abstract

In this paper, we compare the information-theoretic metrics of the Kullback-Leibler (K-L) and Renyi (D) divergence formulations for sensor management. Information-theoretic metrics have been well suited for sensor management as they afford comparisons between distributions resulting from different types of sensors under different actions. The difference in distributions can also be measured as entropy formulations to discern the communication channel capacity (i.e., Shannon limit). In this paper, we formulate a sensor management scenario for target tracking and compare various metrics for performance evaluation as a function of the design parameter (D) so as to determine which measures might be appropriate for sensor management given the dynamics of the scenario and design parameter.