Distributed Greedy Sensor Scheduling for Model-based Reconstruction of Space-Time Continuous Physical Phenomena
A novel distributed sensor scheduling method for large-scale sensor networks observing space-time continuous physical phenomena is introduced. In a first step, the model of the distributed phenomenon is spatially and temporally decomposed leading to a linear probabilistic finite-dimensional model. Based on this representation, the information gain of sensor measurements is evaluated by means of the so-called covariance reduction function. For this reward function, it is shown that the performance of the greedy sensor scheduling is at least half that of the optimal scheduling considering long-term effects. This finding is the key for distributed sensor scheduling, where a central processing unit or fusion center is unnecessary, and thus, scaling as well as reliability is ensured. Hence, greedy scheduling in combination with a proposed hierarchical communication scheme requires only local sensor information and communication.
|Zugehörige Institution(en) am KIT
||Institut für Anthropomatik (IFA)
KITopen ID: 1000034957
||Proceedings of the 12th International Conference on Information Fusion (Fusion 2009). Seattle, Washington, USA, 06.- 09.07.2009
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