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计算机工程 ›› 2017, Vol. 43 ›› Issue (12): 108-114. doi: 10.3969/j.issn.1000-3428.2017.12.021

• 移动互联与通信技术 • 上一篇    下一篇

周期线性调频干扰信号分数阶频谱分析与参数估计方法

周新 1,2,姚富强 2,牛英滔 2,贾录良 1   

  1. (1.解放军理工大学 通信工程学院,南京 210007; 2.南京电讯技术研究所,南京 210007)
  • 收稿日期:2016-11-15 出版日期:2017-12-15 发布日期:2017-12-15
  • 作者简介:周新(1987—),男,硕士,主研方向为无线通信抗干扰;姚富强,研究员、博士后;牛英滔,高级工程师;贾录良,博士。
  • 基金资助:
    国家自然科学基金(61401505)。

Spectrum Analysis and Parameter Estimation Method of Periodic Liner Frequency-modulated Jamming Signal in Fractional Order

ZHOU Xin  1,2,YAO Fuqiang  2,NIU Yingtao  2,JIA Luliang  1   

  1. (1.Institute of Communication Engineering,PLA University of Science and Technology,Nanjing 210007,China; 2.Nanjing Telecommunication Technology Institute,Nanjing 210007,China)
  • Received:2016-11-15 Online:2017-12-15 Published:2017-12-15

摘要: 针对跨周期的线性调频干扰信号的检测和参数估计问题,提出一种分数阶频谱分析与参数估计方法。以采样数据横跨2个周期为例,分析采样的周期线性调频干扰信号在分数阶傅里叶变换域的频谱分布特征,2个周期内的频谱重叠宽度与分数阶旋转角α和各周期内数据长度的关系,以及频谱尖峰发生偏移的条件。推导在离散分数阶傅里叶变换中各参数间的相互关系,得出采用快速解线性调频技术预估调频率的原因。实验结果表明,在2种仿真情况下,该方法都具有较高的参数估计精度。

关键词: 周期线性调频信号, 抗干扰通信, 分数阶傅里叶变换, 频谱特征, 参数估计

Abstract: For the detection and parameter estimation problem of Linear Frequency Modulated(LFM) interference signals over periodic periods,this paper proposes a fractional spectrum analysis and parameter estimation method.Taking the sampled data across two period as an example,the spectrum distribution characteristics of the sampled periodic linear frequency-modulated signal in the fractional Fourier domain,the relationship of the spectrum overlap width,the fractional rotation angle α and data length in each cycle of two periodic spectrum,and the conditions of the peak shifting are analyzed.The relationship among each parameter is inferred in the digital fractional Fourier transform,as well as the reason of the frequency modulation prediction by fast linear frequency modulation technique.Experimental results show that the proposed method has higher accuracy in parameter estimation in two simulation cases.

Key words: periodic Liner Frequency Modulated(LFM) signal, anti-jamming communication, Fractional Fourier Transform(FrFT), spectrum characteristic, parameter estimation

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