The Cauchy-Schwarz Divergence for Assessing Situational Information Gain
AIR FORCE RESEARCH LAB KIRTLAND AFB NM
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In this paper, we consider the evaluation of information divergence and information gain as they apply to a hybrid random variable i.e. a random variable which has both discrete and continuous elements for multi-target tracking problems. In particular, we develop a closed-form solution for the Cauchy- Schwarz information divergence under the assumption that the continuous element of the random variable may be represented by a Gaussian mixture distribution and present the associated relationships for evaluating the Cauchy-Schwarz information gain. The developed information gain relationships are applied to a 0-1 target tracking problem common to space object tracking to determine the sensitivities to the information gain due to probability of detection, prior probability of object existence and measurement noise.