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Sensor configuration and activation for field detection in large sensor arrays (2005)
| Content Provider | CiteSeerX |
|---|---|
| Author | Zhang, Xin Tong, Lang Poor, H. Vincent Sung, Youngchul |
| Abstract | Abstract—The problem of sensor configuration for the detection of correlated random fields using large sensor arrays is considered. Using error exponents that characterize the asymptotic behavior of the optimal detector, the detection performance of different sensor configurations is analyzed and compared. The dependence of the optimal configuration on parameters such as sensor signal-to-noise ratio (SNR), field correlation, etc., is examined, yielding insights into the most effective choices for sensor selection in various operating conditions. Simulation results validate the analysis based on asymptotic results for finite sample cases. Index Terms—Correlated signal, error exponent, Gauss– Markov field, Neyman–Pearson detection, optimal sampling, |
| File Format | |
| Publisher Date | 2005-01-01 |
| Publisher Institution | in Proc. 2005 Information Processing in Sensor Networks (IPSN |
| Access Restriction | Open |
| Subject Keyword | Asymptotic Behavior Correlated Random Field Field Detection Detection Performance Finite Sample Case Optimal Sampling Optimal Detector Gauss Markov Field Index Term Large Sensor Array Sensor Signal-to-noise Ratio Field Correlation Effective Choice Error Exponent Neyman Pearson Detection Simulation Result Optimal Configuration Asymptotic Result Different Sensor Configuration Sensor Selection Sensor Configuration |
| Content Type | Text |
