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An application of fuzzy mathematics in ADS-B data validation

机译:模糊数学在ADS-B数据验证中的应用

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Automatic Dependent Surveillance - Broadcast (ADS-B) is providing significant operational enhancements to military and civilian applications, however, there are still security problems, such as the data can be falsified and the message can be received without authorization, which can be obstacles to the development of ADS-B. This paper proposed fuzzy mathematics application related theory in connection with the issue that ADS-B data can be falsified, through methods such as building fuzzy factor sets, choosing membership functions, allocating fuzzy factor weight sets, verifying track membership degree, etc., conduct dependent verification on ADS-B track data. The simulation results showed that this method is relatively effective and real-timed, which can meet the requirements for the reliability verification on the data.
机译:自动依赖监视 - 广播(ADS-B)正在为军事和民用应用提供重大的操作增强,但是,仍存在安全问题,例如数据可以伪造,并且可以在没有授权的情况下收到消息,这可能是障碍物ADS-B的发展。本文提出了模糊数学应用程序相关理论与ADS-B数据可以伪造的问题,通过建筑模糊因子集,选择隶属函数,分配模糊因子重量集,验证轨道成员度等,进行依赖于ADS-B轨道数据的验证。仿真结果表明,该方法相对有效和实时,可以满足数据对数据的可靠性验证的要求。

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