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- W2538439786 abstract "A generalized likelihood ratio test (GLRT) based decision fusion method that uses quantized data from local sensors is proposed to jointly detect and localize a target in a wireless sensor field. The signal intensity is assumed to be inversely proportional to a power of the distance from the target. The GLRT, its corresponding maximum likelihood (ML) estimator, and the Cramer-Rao lower bound (CRLB) are derived. Simulation results show that this fusion rule has a significantly improved detection performance, compared with the counting rule (for hard local decisions) or the intuitive fusion rules based on the average of sensor data (for soft local decisions)." @default.
- W2538439786 created "2016-10-28" @default.
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- W2538439786 date "2006-01-01" @default.
- W2538439786 modified "2023-09-26" @default.
- W2538439786 title "Joint Detection and Localization in Sensor Networks Based on Local Decisions" @default.
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- W2538439786 doi "https://doi.org/10.1109/acssc.2006.354803" @default.
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