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Emitter recognition using fuzzy inference system

机译:基于模糊推理系统的辐射源识别

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Emitter recognition is the problem of classifying the radar type, from intercepted radar signals. This capability is crucial for classifying approaching enemy ships and aircrafts. The sensed parameters may vary from their actual or reported values because of man-made variations in the form of agility or staggering. Another cause of variation could be dispersion because of atmospheric effects and equipment noise. Associating the measured radar parameter set with a know sighting is a pattern recognition problem in multi-dimensional space. Various research authors have attacked the problem with various data association tools with different merits and de-merits. Most of them are marred by the massive computing power required and unrealistically large training data requirements. In this paper a simple but elegant technique is proposed to solve the above problem using well-established framework of fuzzy logic.
机译:发射器识别是根据拦截的雷达信号对雷达类型进行分类的问题。此功能对于对接近的敌舰和飞机进行分类至关重要。由于敏捷或错开形式的人为变化,感测到的参数可能会与实际值或报告值有所不同。造成变化的另一个原因可能是由于大气影响和设备噪音造成的分散。将测得的雷达参数集与已知瞄准点相关联是多维空间中的模式识别问题。各种各样的研究作者使用具有不同优缺点的各种数据关联工具来攻击该问题。它们中的大多数受到所需的强大计算能力和不切实际的大型培训数据要求的损害。在本文中,提出了一种简单而完善的技术,即使用已建立好的模糊逻辑框架来解决上述问题。

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