摘要
本文针对基于数字射频存储(DRFM)转发的宽带距离-速度(RGS-VGS)同步欺骗干扰的识别问题,建立了宽带RGS-VGS干扰的量化模型,并利用干扰的量化特性提出了一种基于神经网络(BP)的干扰识别方法。宽带干扰信号经DRFM量化后,其频谱中包含一系列假谱,假谱的位置与量化位数有关,其谱宽及调频率都变大。利用干扰误差角(JSEA)衡量信号频谱间的差异程度,并作为神经网络识别的特征参数。实验结果表明,在低量化位数条件下,宽带干扰能够在较低的信噪比条件下被正确识别。
引文
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