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基于FRFT的几种典型相位编码信号检测与参数估计
引用本文:徐会法,胡晓峰,张明智. 基于FRFT的几种典型相位编码信号检测与参数估计[J]. 兵工学报, 2012, 33(9): 1048-1054
作者姓名:徐会法  胡晓峰  张明智
作者单位:国防大学信息作战与指挥训练教研部,北京100091;海军航空工程学院电子信息工程系,山东烟台264001;国防大学信息作战与指挥训练教研部,北京,100091
摘    要:多相编码(Frank码、P1码、P2码、P3码与P4码)信号是一类典型的低截获概率雷达信号。针对该类信号的检测与参数估计,分析了多相编码信号的时频分布特征,讨论了多相编码信号在分数阶Fourier域的频谱分布特征,并以Frank码信号为例,推导出多相编码信号的主要特征参数的估计表达式。提出了一种基于分数阶Fourier变换(FRFT)的多相编码信号检测与参数估计算法。该算法给出一种利用FRFT估计多相编码信号载频的方法。最后,仿真结果表明该算法在低信噪比(SNR)条件下对多相编码信号仍具有较好的检测和参数估计效果。

关 键 词:雷达工程  多相编码信号  分数阶Fourier变换  信号检测  参数估计

Detection and Parameter Estimation of Polyphase Code Signals Based on Fractional Fourier Transform
XU Hui-fa , HU Xiao-feng , ZHANG Ming-zhi. Detection and Parameter Estimation of Polyphase Code Signals Based on Fractional Fourier Transform[J]. Acta Armamentarii, 2012, 33(9): 1048-1054
Authors:XU Hui-fa    HU Xiao-feng    ZHANG Ming-zhi
Affiliation:(1. Department of Information Operation & Command Training, National University of Defense Technology, Beijing 100091, China;2. Department of Electronic and Information Engineering, Naval Aeronautical Engineering Institute, Yantai 264001, Shandong, China)
Abstract:The polyphase code (Frank, P1, P2, P3 and P4 code) signals are a kind of typical low probability of intercept (LPI) radar signals. For the detection and parameter estimation of this kind of signals, the time-frequency distribution characteristics of the polyphase code signals were analyzed; the fractional spectrum characteristics of the polyphase code signals were also analyzed and the parameter estimation expressions of the polyphase code signals were deduced, taking Frank code signal for example. An algorithm for detection and parameters estimation of the polyphase code signals was proposed based on fractional Fourier transform (FRFT). And the algorithm first presents a method to estimate the carrier frequency of the polyphase code signals. Finally, simulations verifying the algorithm still has better signal detection and parameter estimation effect in low signal-to-noise ratios (SNR) condition.
Keywords:
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