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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:自动相关监视-广播(ADS-B)为军事和民用应用提供了重要的操作增强功能,但是,仍然存在安全问题,例如,数据可能被伪造,未经授权就可以接收消息,这可能成为障碍。开发ADS-B。提出了通过建立模糊因子集,选择隶属度函数,分配模糊因子权重集,验证轨道隶属度等方法对ADS-B数据进行伪造的模糊数学应用相关理论。对ADS-B跟踪数据的依赖验证。仿真结果表明,该方法相对有效,实时,可以满足数据可靠性验证的要求。

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