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A fuzzy pattern recognition method of radar signal based on neural network

机译:基于神经网络的雷达信号模糊模式识别方法

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Radar signal recognition is an important step of radar countermeasure processing. The classical recognition method is called weight distance, in which the feature parameter weights are obtained by expert and then the weight distance of unknown radar signal and signal template in database is computed. For it existing subjectivity in setting of feature parameter weights with classical recognition method, and the computing method of recognition is too simple, all of which make recognition result can't reflect the true fact objectively. Considering this point, a fuzzy pattern recognition method based on neural network getting weights to radar signal recognition is studied in this paper, the feature parameter weights in this method are fixed on by neural network and then the unknown radar signal is recognized by fuzzy pattern recognition method. Simulation experiment and its result show the method in this paper is practicable and more reliable compared with classical method.
机译:雷达信号识别是雷达对策处理的重要步骤。经典的识别方法称为权重距离,该方法是由专家获得特征参数权重,然后计算数据库中未知雷达信号和信号模板的权重距离。由于采用经典的识别方法来设置特征参数权重存在主观性,并且识别的计算方法过于简单,所有这些使得识别结果不能客观地反映真实情况。考虑到这一点,本文研究了一种基于神经网络的权重对雷达信号识别的模糊模式识别方法,通过神经网络固定该方法的特征参数权重,然后通过模糊模式识别来识别未知的雷达信号。方法。仿真实验及其结果表明,与经典方法相比,本文方法是可行的,更可靠。

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