【摘 要】
：
Data selection-based summation fusion (DSSF) was developed to overcome the shortcomings of previously developed likelihood ratio tests based on channel statisti
【机 构】
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Department of Electronic Engineering,The First Department
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Data selection-based summation fusion (DSSF) was developed to overcome the shortcomings of previously developed likelihood ratio tests based on channel statistics (LRT-CS) for the problem of fusing censored binary decisions transmitted over Nakagami fading channels in a wireless sensor network (WSN).The LRT-CS relies on detection probabilities of the local sensors, while the detection probabilities are a pri-ori unknown for uncooperative targets. Also, for Nakagami fading channels, the LRT-CS involves an infinite series, which is cumbersome for real-time application. In contrast, the DSSF only involves data comparisons and additions and does not require the detection probabilities of local sensors. Furthermore, the perform-ance of DSSF is only slightly degraded in comparison with the LRT-CS when the detection probabilities of local sensors are a priori unknown. Therefore, the DSSF should be used in a WSN with limited resources.
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