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Convex Optimization Approaches to Long-Term Sensor Scheduling

Technischer Bericht

Links:
Autor:

Marco F. Huber

Quelle:

Technischer Bericht IES-2009-01. In: Jürgen Beyerer, Marco Huber (Hrsg.), Proceedings of the 2009 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory, KIT Scientific Publishing, 2009.

Seiten:

1-16

The optimization over long time horizons in order to consider long-term effects is of paramount importance for effective sensor scheduling in multi-sensor systems like sensor arrays or sensor networks. Determining the optimal sensor schedule, however, is equivalent to solving a binary integer program, which is computationally demanding for long time horizons and many sensors. For linear Gaussian models, two efficient long-term sensor scheduling approaches are proposed in this report. The first approach determines approximate but close to optimal sensor schedules via convex optimization. The second approach combines convex optimization with a branch-and-bound search for efficiently determining the optimal sensor schedule. Both approaches are compared by means of numerical simulations.