Information-based sensor management

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Abstract
The problem of intelligent use of sensors in a multi-sensor, multi-target surveillance system is discussed. The problem is to make the optimal assignment of targets to sensors subject to given constraints on sensor capacity and for a given definition of optimal. We have found previous work on the sensor management problem to have deficiencies due to the way information is used to optimize the assignment. There are numerous formulations of such `information' based approaches in the literature. This paper attempts to put the problem on a first principles basis. The approach taken here it to determine the predicted gain in information content of a track j after it is updated with data from sensor i for all pairs i,j. This information content can be predicted without making the actual observation by using the properties of the Kalman covariance matrix. The particular assignment of tracks to sensors that maximizes the total information gain subject to the constraints on the sensors is then generated using linear programming methods.

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