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
A concise fractional Fourier transform （CFRFT） is proposed to detect the linear frequency-modulated （LFM） signal with low signal to noise ratio （SNR）. The frequency axis in time-frequency plane of the CFRFT is r...A concise fractional Fourier transform （CFRFT） is proposed to detect the linear frequency-modulated （LFM） signal with low signal to noise ratio （SNR）. The frequency axis in time-frequency plane of the CFRFT is rotated to get the spectrum of the signal in different an- gles using chirp multiplication and Fourier transform （FT）. For LFM signal which distributes as a straight line in time-frequency plane, the CFRFT can gather the energy in the corresponding angle as a peak and improve the detection SNR, thus the LFM signal of low SNR can be de- tected. Meanwhile, the location of the peak value relates to the parameters of the LFM signal. Numerical simulations and experimental results show that, the proposed method can be used to efficiently detect the LFM signal masked by noise and to estimate the signal＇s parameters accurately. Compared with the conventional fractional Fourier transform （FRFT）, the CFRFT reduces the transform complexity and improves the real-time detection performance of LFM signal.展开更多
针对甚小频偏线性调频(very minimum frequency shift-linear frequency modulation,VMFS-LFM)信号对应的分数阶傅里叶(fractional fourier transform,FrFT)域估计参数的绝对值接近1而导致估计性能降低的问题,在借鉴基于FrFT的LFM信号...针对甚小频偏线性调频(very minimum frequency shift-linear frequency modulation,VMFS-LFM)信号对应的分数阶傅里叶(fractional fourier transform,FrFT)域估计参数的绝对值接近1而导致估计性能降低的问题,在借鉴基于FrFT的LFM信号参数估计方法的基础上,采用m倍抽取(m time decimation,mTD)作为预处理方法,提出基于mTD-FrFT的VMFS-LFM信号参数估计方法.理论分析和实验结果表明:mTD预处理过程可增大VMFS-LFM信号和近参数多分量LFM信号的调频斜率在FrFT域的分辨率,使基于mTD-FrFT的参数估计方法可对VMFS-LFM信号和相近参数多分量LFM信号进行有效参数估计.展开更多
针对线性调频(Linear Frequency Modem,LFM)信号的快速检测和高精度参数估计问题,在分析LFM信号特征和分数阶傅里叶变换(FrFT)原理的基础上,基于快速解线性调频技术,提出了一种LFM信号检测和参数估计算法,该算法将LFM信号检测由二维搜...针对线性调频(Linear Frequency Modem,LFM)信号的快速检测和高精度参数估计问题,在分析LFM信号特征和分数阶傅里叶变换(FrFT)原理的基础上,基于快速解线性调频技术,提出了一种LFM信号检测和参数估计算法,该算法将LFM信号检测由二维搜索转换为一维搜索,从而有效地减少了运算量。仿真结果表明,算法在低信噪比下具有良好的参数估计性能。展开更多
基金supported by the National Natural Science Foundation of China(11434012)
文摘A concise fractional Fourier transform （CFRFT） is proposed to detect the linear frequency-modulated （LFM） signal with low signal to noise ratio （SNR）. The frequency axis in time-frequency plane of the CFRFT is rotated to get the spectrum of the signal in different an- gles using chirp multiplication and Fourier transform （FT）. For LFM signal which distributes as a straight line in time-frequency plane, the CFRFT can gather the energy in the corresponding angle as a peak and improve the detection SNR, thus the LFM signal of low SNR can be de- tected. Meanwhile, the location of the peak value relates to the parameters of the LFM signal. Numerical simulations and experimental results show that, the proposed method can be used to efficiently detect the LFM signal masked by noise and to estimate the signal＇s parameters accurately. Compared with the conventional fractional Fourier transform （FRFT）, the CFRFT reduces the transform complexity and improves the real-time detection performance of LFM signal.
文摘针对甚小频偏线性调频(very minimum frequency shift-linear frequency modulation,VMFS-LFM)信号对应的分数阶傅里叶(fractional fourier transform,FrFT)域估计参数的绝对值接近1而导致估计性能降低的问题,在借鉴基于FrFT的LFM信号参数估计方法的基础上,采用m倍抽取(m time decimation,mTD)作为预处理方法,提出基于mTD-FrFT的VMFS-LFM信号参数估计方法.理论分析和实验结果表明:mTD预处理过程可增大VMFS-LFM信号和近参数多分量LFM信号的调频斜率在FrFT域的分辨率,使基于mTD-FrFT的参数估计方法可对VMFS-LFM信号和相近参数多分量LFM信号进行有效参数估计.
文摘针对线性调频(Linear Frequency Modem,LFM)信号的快速检测和高精度参数估计问题,在分析LFM信号特征和分数阶傅里叶变换(FrFT)原理的基础上,基于快速解线性调频技术,提出了一种LFM信号检测和参数估计算法,该算法将LFM信号检测由二维搜索转换为一维搜索,从而有效地减少了运算量。仿真结果表明,算法在低信噪比下具有良好的参数估计性能。
