Yan Yongsheng, Wang Haiyan, Shen Xiaohong, Zhong Xionghu
School of Marine Science and Technology, Northwestern Polytechnical University,127 Youyi West Road, Xi\'an 710072, China.
School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
Sensors (Basel). 2015 Aug 5;15(8):19157-80. doi: 10.3390/s150819157.
Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones.
本文研究了非理想信道下传感器网络中分布式检测的决策融合问题。通常，局部决策被传输到融合中心（FC）并进行解码，然后应用融合规则以实现全局决策。我们提出一种基于最优似然比检验（LRT）的融合规则，以考虑由于调制、接收模式和通信信道导致的解码二进制数据的不确定性。采用平均误码率（BER）来表征这种不确定性。此外，在局部检测性能指标不相同和相同的情况下，均对检测性能进行了分析。另外，将所提方法的性能与现有的最优和次优LRT融合规则进行了比较。结果表明，与现有规则相比，所提融合规则具有更强的鲁棒性。
