In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter e...In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter estimation method for LFM signals with a Duffing oscillator based on frequency periodicity is proposed in this paper.This method utilizes the characteristic that the output signal of the Duffing oscillator excited by the LFM signal changes periodically with frequency,and the modulation period of the LFM signal is estimated by autocorrelation processing of the output signal of the Duffing oscillator.On this basis,the corresponding relationship between the reference frequency of the frequencyaligned Duffing oscillator and the frequency range of the LFM signal is analyzed by the periodic power spectrum method,and the frequency information of the LFM signal is determined.Simulation results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.展开更多
基于分数阶傅里叶变换(Fractional Fourier Transform,FRFT)对线性调频(Linear Frequency Modulated,LFM)信号参数进行估计,问题关键是确定FRFT最佳阶数,根据误差迭代思想提出新的参数估计算法,该算法利用归一化带宽和旋转角的转化关系...基于分数阶傅里叶变换(Fractional Fourier Transform,FRFT)对线性调频(Linear Frequency Modulated,LFM)信号参数进行估计,问题关键是确定FRFT最佳阶数,根据误差迭代思想提出新的参数估计算法,该算法利用归一化带宽和旋转角的转化关系,由估计误差推算角度差值,有效降低了运算量,不需要调频斜率正负的先验信息,改进的对数搜索算法可以进一步提高参数估计结果的稳定性和可靠性。仿真结果表明,信噪比在-8 dB以上时该方法在高效率的前提下仍具有良好的参数估计性能,平均估计误差在1%以内,估计结果接近Cramer-Rao下限,满足工程实时处理需求。展开更多
首先介绍了相位编码与线性调频(Linear frequency modulation and binary phase shift keying,LFM-BPSK)复合调制信号的模型,并分析了其相位特征及概率密度函数,然后通过分段滤波提高信号的输出信噪比。采用二叉树方法,基于相位展开和...首先介绍了相位编码与线性调频(Linear frequency modulation and binary phase shift keying,LFM-BPSK)复合调制信号的模型,并分析了其相位特征及概率密度函数,然后通过分段滤波提高信号的输出信噪比。采用二叉树方法,基于相位展开和瞬时频率对LFM-BPSK复合调制信号、BPSK信号和LFM信号进行了识别,并讨论和分析了纽曼-皮尔逊(N-P)准则下识别门限的选取。接着对LFM-BPSK复合调制信号进行参数估计;最后用Matlab对LFM-BPSK复合调制信号的识别进行了仿真验证,并对识别后的信号进行了参数估计的仿真。结果表明,本文方法在较低信噪比下仍能实现较好的识别性能和参数估计精度。展开更多
本文研究了线性调频(LFM,Linear Frequency Modulation)信号盲处理结果的可靠性检验问题,提出了一种基于纽曼皮尔逊(NP,Neyman-Pearson)准则的检验算法.先根据调制识别结果对应的信号模型构造参考信号,通过分析不同假设下参考信号与观...本文研究了线性调频(LFM,Linear Frequency Modulation)信号盲处理结果的可靠性检验问题,提出了一种基于纽曼皮尔逊(NP,Neyman-Pearson)准则的检验算法.先根据调制识别结果对应的信号模型构造参考信号,通过分析不同假设下参考信号与观测信号相关累加值概率分布参数的差异,利用NP准则构建检验统计量并确定相应的门限,对LFM信号盲处理结果的可靠性进行检验.计算机仿真结果表明,本算法在较低信噪比条件下,可实现对LFM信号盲处理结果的可靠性检验.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61973037)。
文摘In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter estimation method for LFM signals with a Duffing oscillator based on frequency periodicity is proposed in this paper.This method utilizes the characteristic that the output signal of the Duffing oscillator excited by the LFM signal changes periodically with frequency,and the modulation period of the LFM signal is estimated by autocorrelation processing of the output signal of the Duffing oscillator.On this basis,the corresponding relationship between the reference frequency of the frequencyaligned Duffing oscillator and the frequency range of the LFM signal is analyzed by the periodic power spectrum method,and the frequency information of the LFM signal is determined.Simulation results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.
文摘首先介绍了相位编码与线性调频(Linear frequency modulation and binary phase shift keying,LFM-BPSK)复合调制信号的模型,并分析了其相位特征及概率密度函数,然后通过分段滤波提高信号的输出信噪比。采用二叉树方法,基于相位展开和瞬时频率对LFM-BPSK复合调制信号、BPSK信号和LFM信号进行了识别,并讨论和分析了纽曼-皮尔逊(N-P)准则下识别门限的选取。接着对LFM-BPSK复合调制信号进行参数估计;最后用Matlab对LFM-BPSK复合调制信号的识别进行了仿真验证,并对识别后的信号进行了参数估计的仿真。结果表明,本文方法在较低信噪比下仍能实现较好的识别性能和参数估计精度。
文摘本文研究了线性调频(LFM,Linear Frequency Modulation)信号盲处理结果的可靠性检验问题,提出了一种基于纽曼皮尔逊(NP,Neyman-Pearson)准则的检验算法.先根据调制识别结果对应的信号模型构造参考信号,通过分析不同假设下参考信号与观测信号相关累加值概率分布参数的差异,利用NP准则构建检验统计量并确定相应的门限,对LFM信号盲处理结果的可靠性进行检验.计算机仿真结果表明,本算法在较低信噪比条件下,可实现对LFM信号盲处理结果的可靠性检验.
