目标识别决策层融合神经网络算法研究
RESEARCH ON THE NEURAL NETWORK ALGORITHM FOR THE DECISION FUSION OF TARGET RECOGNITION
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摘要: 该文针对毫米波／红外传感器融合目标识别问题，提出一种新的用于决策层目标识别的神经网络融合算法。该网络结构新颖，网络训练时修改的是门限而不是连接权值。融合后的识别率可比毫米波和红外子源提高9.7％到11.3％，因此，该算法是有效可行的。
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关键词:
- 神经网络;决策层融合;目标识别
Abstract: In the light of the target recognition based on MMW/IR fusion,a new neural network algorithm for the decision fusion is presented in this paper.The architecture of this network is novel.It is the thresholds,not the conjunction weights,that are modified,when the network is being trained.The mean correct recognition rate after fusion is higher than that of MMW and IR subsources by 9.7% and 11.3% respectively,which indicates this algorithm is effective and feasible. -
杨静宇，邬永革，等．战场数据融合技术．北京：兵器工业出版社，1994，1-11．[2]郁文贤，雍少为，郭桂蓉．信息融合述评．长沙：国防科学技术大学学报，1994，16(3)：1-11．[3]孙红岩，毛士艺．多传感器目标识别的数据融合．电子学报，1995，23(10)：188-193．[4]Pawlak J.A new neural network architecture for the fusion of independent or dependent sensor decisions[J].SPIE.1994,2232:6-16 -
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