Title :
Distributed signal detection under the Neyman-Pearson criterion
Author :
Yan, Qing ; Blum, Rick S.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Lehigh Univ., Bethlehem, PA, USA
fDate :
5/1/2001 12:00:00 AM
Abstract :
A procedure for finding the Neyman-Pearson optimum distributed sensor detectors for cases with statistically dependent observations is described. This is the first valid procedure we have seen for this case. This procedure is based on a theorem proven in this paper. These results clarify and correct a number of possibly misleading discussions in the existing literature. Cases with networks of sensors in fairly general configurations are considered along with cases where the sensor detectors make multiple bit sensor decisions
Keywords :
distributed processing; optimisation; signal detection; Neyman-Pearson criterion; distributed signal detection; multiple bit sensor decisions; optimum distributed sensor detectors; statistically dependent observations; theorem; Detectors; Probability; Random variables; Sensor fusion; Sensor phenomena and characterization; Signal design; Signal detection; Statistical analysis; Testing; Topology;
Journal_Title :
Information Theory, IEEE Transactions on
