基于模糊推理系统的辐射源识别

S. Hassan, A. Bhatti, A. Latif
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引用次数: 11

摘要

辐射源识别是根据截获的雷达信号对雷达类型进行分类的问题。这种能力对于对接近的敌舰和飞机进行分类至关重要。由于人为的敏捷性或错误性的变化,被测参数可能与实际值或报告值有所不同。另一个变化的原因可能是由于大气影响和设备噪声造成的分散。将被测雷达参数集与已知目标相关联是一个多维空间的模式识别问题。不同的研究作者用不同的数据关联工具来解决这个问题,这些工具有不同的优点和缺点。它们中的大多数都被所需的大量计算能力和不切实际的大量训练数据需求所破坏。本文提出了一种简单而优雅的方法,利用模糊逻辑的框架来解决上述问题
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emitter recognition using fuzzy inference system
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
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