Decentralized Detection With Censoring Sensors
| Autor: | S. Appadwedula, Douglas L. Jones, Venugopal V. Veeravalli |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Mathematical optimization
business.industry Decision theory Decision rule Machine learning computer.software_genre Sensor fusion Sensor array Censoring (clinical trials) Signal Processing Artificial intelligence Electrical and Electronic Engineering business computer Wireless sensor network Fusion center Mathematics Optimal decision |
| Zdroj: | IEEE Transactions on Signal Processing. 56:1362-1373 |
| ISSN: | 1941-0476 1053-587X |
| DOI: | 10.1109/tsp.2007.909355 |
| Popis: | In the censoring approach to decentralized detection, sensors transmit real-valued functions of their observations when "informative" and save energy by not transmitting otherwise. We address several practical issues in the design of censoring sensor networks including the joint dependence of sensor decision rules, randomization of decision strategies, and partially known distributions. In canonical decentralized detection problems involving quantization of sensor observations, joint optimization of the sensor quantizers is necessary. We show that under a send/no-send constraint on each sensor and when the fusion center has its own observations, the sensor decision rules can be determined independently. In terms of design, and particularly for adaptive systems, the independence of sensor decision rules implies that minimal communication is required. We address the uncertainty in the distribution of the observations typically encountered in practice by determining the optimal sensor decision rules and fusion rule for three formulations: a robust formulation, generalized likelihood ratio tests, and a locally optimum formulation. Examples are provided to illustrate the independence of sensor decision rules, and to evaluate the partially known formulations. |
| Databáze: | OpenAIRE |
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