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2004
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Entropy-based sensor selection heuristic for target localization

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Entropy-based sensor selection heuristic for target localization
We propose an entropy-based sensor selection heuristic for localization. Given 1) a prior probability distribution of the target location, and 2) the locations and the sensing models of a set of candidate sensors for selection, the heuristic selects an informative sensor such that the fusion of the selected sensor observation with the prior target location distribution would yield on average the greatest or nearly the greatest reduction in the entropy of the target location distribution. The heuristic greedily selects one sensor in each step without retrieving any actual sensor observations. The heuristic is also computationally much simpler than the mutual-information-based approaches. The effectiveness of the heuristic is evaluated using localization simulations in which Gaussian sensing models are assumed for simplicity. The heuristic is more effective when the optimal candidate sensor is more informative. Categories and Subject Descriptors
Hanbiao Wang, Kung Yao, Gregory J. Pottie, Deborah
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where IPSN
Authors Hanbiao Wang, Kung Yao, Gregory J. Pottie, Deborah Estrin
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