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水下潜器多传感器信息融合的不确定性分析 预览

Uncertainty analysis of navigation sensor information fusion for underwater vehicle
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摘要 为了降低水下潜器组合导航模型中传感器信息的不确定性,提出了一种基于证据理论的多传感器信息融合方法。在该算法中,将导航传感器信息数据输入到ELMAN网络来获取D-S证据理论中各传感器故障的基本概率赋值,再利用改进后的证据理论对导航系统的信息进行决策级融合。仿真结果表明,导航传感器信息的不确定性降低到0.001,可以精确检测到故障传感器,有效提高了系统信息的可靠性和对传感器故障的识别能力,为水下潜器精确导航提供了保障。 In order to reduce information uncertainty in integrated navigation model for underwater vehicle, a multi-sensor information fusion algorithm based on evidence theory is presented. In the algorithm, the navigation sensor measured data were input into ELMAN network and used to obtain basic probability assignment for sensor fault in D-S evidence theory. And then the improved evidence theory was used to execute the decision and fusion for navigation information. The simulation results prove that the uncertainty of navigation sensor information is reduced to 0.001, and the fault sensor can be detected. The algorithm can effectively improve the reliability of navigation system information and the recognition of sensor fault, which provides the guarantee for the precise navigation of underwater vehicle.
作者 张涛 齐永奇 郭晓波 ZHANG Tao[1] QI Yong-qi[1] GUO Xiao-bo[2]
出处 《中国惯性技术学报》 EI CSCD 北大核心 2013年第6期共5页 Journal of Chinese Inertial Technology
基金 国家自然科学基金(U1204613/F010810);河南省教育厅科学技术研究重点项目(12A460008);河南省重点科技攻关项目
关键词 水下潜器 信息融合 不确定性 证据理论 神经网络 underwater vehicle information fusion uncertainty analysis evidence theory neural network
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参考文献10

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