conference paper
Dynamic context-aware sensor selection for sequential hypothesis testing
Nurali Virania b, Ji-Woong Leec d, Shashi Phohac d, Asok Raya b
- aDepartment of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA, USA
- bDepartment of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park 16802, USA
- cThe Applied Research Laboratory, The Pennsylvania State University, University Park, PA, USA
- dApplied Research Laboratory, The Pennsylvania State University, University Park 16802, USA
Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive ProcessesInstitute of Electrical and Electronics Engineers2014-12-01 5 citations28 references
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Abstract
Dynamic sensor selection rules are obtained based on a context-aware measurement model in the framework of sequential hypotheses testing. The notion of context incorporates the operational conditions that directly affect sensor measurements. While a random context leads to a Bayesian decision rule, an unknown but nonrandom context yields minimax game-based rules. In either case, the resulting sensor selection rule trades off decision performance against the cost of sensor activation and the uncertainty of the true context.