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FS-DS based Multi-sensor Data Fusion

机译:基于FS-DS的多传感器数据融合

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摘要

Considering the problem of the uncertainty of data in information gathering system, a multi-sensor information fusion method based on fuzzy set and evidence theory (FS-DS) is proposed. The fuzzy support probability of the uncertain information is defined by making using of the correlation function, Then it is received the credibility of the information measured by each sensor form the membership function. And , will the support and confidence into basic probability function. Finally, the sensors with higher measurement precision are identified by D-S evidence combination. The proposed method can improve the problem of the basic probability assignment function is difficult to be determined and the calculation of degree of mutual support is absolute are improved. The practical application verifies that the fusion result has higher accuracy and reliability.
机译:针对信息采集系统中数据不确定性的问题,提出了一种基于模糊集和证据理论的多传感器信息融合方法。利用相关函数定义不确定信息的模糊支持概率,然后通过隶属度函数接收各个传感器测得的信息的可信度。并且,将支持和置信度转换为基本概率函数。最后,通过D-S证据组合识别出具有较高测量精度的传感器。所提出的方法可以改善基本概率分配函数难以确定的问题,并且改进了相互支持度的计算。实际应用验证了融合结果具有较高的准确性和可靠性。

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