FRFT域LFM雷达回波信号的压缩采样模型

针对宽带雷达线性调频信号(Linear Frequency Modulated,LFM)带宽大、采样率高、存储容量要求高的问题,设计了一种基于压缩感知的 LFM雷达回波信号的欠采样整体方案。首先,利用 LFM信号在分数阶傅里叶变换(FRactional Fourier Transform,FRFT)域上良好的能量聚集特点,提出了一种基于DFRFT核矩阵的正交基字典构造方法,在此基字典的基础上利用随机解调器和匹配追踪类算法构建了一个 LFM雷达回波信号的压缩采样和重构系统模型。仿真结果验证了 FRFT域处理 LFM雷达回波信号的可行性和有效性,LFM雷达信号在该正交基字典上的稀疏表示效果要优于现有的波形匹配字典,而且具有更好的抗噪性能和自适应性能。     

基于新型DFrFT的LFM信号参数估计算法

针对传统算法对高调频率线性调频(linear frequency modulation,LFM)信号进行参数估计时误差较大的问题,提出了一种基于新型离散分数阶傅里叶变换(discrete fractional Fourier transform,DFrFT)的LFM信号参数估计算法.新型DFrFT在传统离散算法的基础上...     

基于瞬时互相关和STFT的LFM信号测向算法

现代电子对抗中,实现对线性调频(LFM)信号这种低截获概率雷达信号的精确测向已经非常重要.针对LFM信号提出一种无模糊、高精度的DOA估计算法.该算法首先计算单基线天线接收到的信号的瞬时互相关,然后通过短时傅里叶变换(STFT)提取互相关输出中的单频信号.利用该信号的频率与到达角之间单调的对应关系实现对到达角的无模糊估计.算法克服了相位干涉仪测向算法中存在的多值模糊问题,并且由于只需要单基线天线,所以能够应用于天线孔径尺寸受限的场合.对算法的性能进行了理论分析,推导了测向算法的精度和估计误差,并且理论推导了角度分辨率和测角实时性之间的量化关系,仿真实验结果表明了该算法的正确性和有效性.     

高精度LFM信号参数估计

解线性调频方法是实际工程中常采用的一种估计LFM信号参数的方法,然而该方法需要对调频斜率在一定范围内搜索,运算量大。针对这个问题本文提出了一种改进算法,首先通过计算LFM信号瞬时自相关的FFT得到调频斜率的估计值,然后在此值附近作小范围精细搜索,从而获得高精度的参数估计值。该方法缩小了搜索的范围,在运算量减少的同时,提高了参数的估计精度。仿真结果表明了此方法的有效性。     

改进的三次相位函数法LFM雷达信号参数估计

为了研究对线性调频(LFM)雷达信号的参数估计,提出了利用改进的三次相位函数法对LFM雷达信号进行参数估计.三次相位函数法可提取信号的相位函数的各项系数,并且只需通过二阶非线性变换在信号参数空间形成最大值来进行估计参数,具有较高的精度和良好的低信噪比能力,但是计算量较大.针对三次相位函数法计算量大的问题,提出调频斜率搜索范围设定准则及双尺度调频斜率搜索法,可减少大量计算量,同时保持了低信噪比下的算法精度.仿真测试结果表明,新算法有效地减小了计算量,并且保证了低信噪比下的算法精度,算法性能得到了提高.     

基于FrFT和子空间正交的LFM信号参数估计

基于分数阶Fourier变换和子空间正交性,提出了一种低信噪比下线性调频信号检测与参数估计方法。讨论过程中将线性调频信号通过适当的分数阶Fourier变换得到一个单频复正弦信号,在此基础上,利用信号子空间与噪声子空间的正交性处理其正弦信号,再对线性调频信号的检测和参数估计转化为函数极值求解;最后,利用计算机模拟证实了方法的有效性。     

分数阶自相关和FrFT的LFM信号参数估计

基于分数阶自相关和分数阶傅里叶变换的特点,提出了一种LFM信号检测与参数估计方法。相对分数阶傅里叶二维扫描法和匹配傅里叶变换,所提方法将检测与参数估计的二维搜索变为一维搜索,快速实现信号检测和参数估计,在多分量LFM信号情况下借助"Clean"的方法来抑制强分量对弱分量的干扰。计算机仿真表明了该算法在低信噪比多分量LFM信号检测与参数估计中的有效性。     

一种信号无间隔脉冲频域分析方法研究

提出了一种对信号频谱的估算方法———无间隔脉冲频域分析(noninterval pulse frequency analyse,NPFA)方法,从理论上证明了其正确性,给出了若干仿真实例;着重在计算量、计算精度、栏栅效应上与离散傅里叶变换(discreteFourier transform,DFT)及快速傅里叶变换(fast Fourier transform,FFT)分别做了比较,结果表明:在估算短数据个别频点的频谱时,该方法有优于DFT及FFT的特点。     

基于mTD-FrFT的VMFS-LFM信号参数估计方法

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.     

基于时频分析的LFM信号检测与参数估计

基于Radon Wigner变换、分数阶Fourier变换与时频分布的关系,利用其对线性调频(linearityfrquencymodulation,LFM)信号良好的时频聚集性,通过计算Radon Wigner变换或分数阶Fourier变换,对线性调频信号LFM信号进行检测和参数估计。理论分析和计算机仿真证明:2种方法对于LFM信号的分析好于Wigner Ville变换等常用的时频变换。     

Propagator method for multiple-parameter estimation of LFM signal for conformal array antenna

A multiple parameter estimation method for the LFM signal for the conformal array antenna is presented. By employing the energy focusing property of certain-ordered-FRFT to the LFM signal, multiple components blended in received data are separated in the FRFT domain, and hence the simplified data model is acquired, because of which the complicated parameter match is avoided, and then the DOA and polarization estimation is performed by using the PM algorithm. Benefiting from the avoiding of parameter matching and high dimensional eigen-value decomposition, the complexity and computational burden of the algorithm is remarkably controlled. Simulation results show that the proposed algorithm has an approximate performance with a much lower computation burden than ESPRIT.     

Chirp-Rate Resolution of Fractional Fourier Transform in Multi-component LFM Signal

Distinguishing close chirp-rates of different linear frequency modulation (LFM) signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-component LFM signal were used by discrete fast fractional Fourier transform (FrFT). Then the expression of chirp-rate resolution in fractional Fourier domain (FrFD) was deduced from discrete normalize time-frequency distribution, when multi-component LFM signal had only one center frequency. Furthermore, the detail influence of the sampling time, sampling frequency and chirp-rate upon the resolution was analyzed by partial differential equation. Simulation results and analysis indicate that increasing the sampling time can enhance the resolution, but the influence of the sampling frequency can be omitted. What’s more, in multi-component LFM signal, the chirp-rate resolution of FrFT is no less than a minimal value, and it mainly dependent on the biggest value of chirp-rates, with which it has an approximately positive exponential relationship.     

基于AF切片与FrFT的STLFM信号检测与参数估计算法

针对基于Radon-Ambiguity变换(RAT)和分数阶Fourier变换(FrFT)的对称三角线性调频(STLFM)信号参数估计算法运算量较大的问题,在分析RAT变换估计调频斜率和STLFM信号模糊函数特征基础上提出了一种基于模糊函数(AF)切片和FrFT的STLFM信号参数估计新算法。该算法首先通过对观测信号固定时延点AF切片的计算估计出调频斜率,然后得到相应的FrFT最优变换阶数,最后利用两次FrFT估计出STLFM信号的调频带宽、调频周期和中心频率等参数。整个算法只需3次FFT的计算量即可估计出STLFM信号的所有参数。仿真实验表明了该算法能实现STLFM信号参数的快速有效估计。     

小波域的最大似然调制分类

针对电子战领域中的调制类型识别问题,提出了一种把通信信号变换到小波域下的最大似然调制分类算法．通过分析MPSK信号在Haar小波基下的小波变换系数同其相位参数之间的关系,把MPSK信号的小波变换系数用广义高斯概率分布进行建模来得到MPSK信号的最大似然分类函数．同常规的最大似然分类算法相比新方法所需的先验信息少．计算机仿真结果表明,这种算法在低信噪比下仍然能获得好的正确分类性能．     

基于分数阶傅里叶变换的LFM干扰抑制算法

针对利用分数阶傅里叶变换(fractional Fourier transform,FrFT)进行干扰抑制时门限阈值设定的难题,为有效抑制DS/FH系统中的线性调频(linear frequency modulated,LFM)干扰,通过深入分析DS/FH和LFM信号的FrFT性质,提出了一种新的LFM干扰抑制算法,该算法充分利用FrFT时频面坐标轴旋转性质,通过计算信号的不同阶次FrFT并搜索其峰值,确定信号最优FrFT阶次,完成对LFM干扰信号的判别,最后采用频域陷波来抑制LFM干扰。理论分析和仿真实验表明,该算法能够有效的剔除DS/FH系统中的LFM干扰信号,不需要阈值门限设定,算法具有较好的稳健性和普适性。     

Novel LFM Jammer Suppression Algorithm for DSSS in FRFT Domain

A novel algorithm is proposed to resolve the defects in the traditional linear frequency modulation (LFM) jamming suppression algorithm in the fractional Fourier transform (FRFT) domain. The traditional LFM jamming suppression algorithm in the FRFT domain has some defects. For example, the exact threshold is difficult to set and both the signal-to-noise ratio (SNR) loss and spectrum leakage are serious in strong jamming-to-signal ratio (JSR) situations. Windowing, overlapping and inverse windowing techniques are used in the FRFT domain to reduce the spectrum leakage and the SNR loss. Under the condition that only the direct sequence spread spectrum (DSSS) signal and white Gaussian noise are present, the amplitude of the received signal after FRFT is assumed to be Rayleigh distributed. Based on the distribution characteristic, hypothesis testing is used to suppress the jamming spectrum using the algorithm. Simulation results show that the performance of proposed algorithm is better than that of the conventional algorithms, especially in a strong jamming and multi component LFM jamming environment.     

基于延时相关和FRFT的编队目标架次分辨方法

为较好满足窄带雷达的防空作战需求,提出了一种基于延时相关和分数阶傅里叶变换(FRFT)的空中编队目标架次分辨方法.该方法首先利用延时相关法粗略估计出回波信号的多普勒调频斜率,依据调频斜率和FRFT阶次的对应关系,获得最优变换阶次的粗略值;然后以FRFT后信号的熵值为最小化目标函数,提出一种精确搜索最优变换阶次算法,并以...     

Novel method for frequency hopping signals blind identification in the compressed domain

A novel method to blindly identify frequency hopping signals is presented in the compressed domain. The samples obtained by compressive sampling effectively maintain the structure of and the information on the original signal, so the task of identification of the original signal could be done by directly processing the sampling values. The method is based on the difference in numerical characteristic between sampling values. According to the different characteristics of the expectation of sampling values under different hypotheses, identification is accomplished by using the deviation of the actual sampling values from the expectations under the corresponding hypothesis as the criterion. Without reconstructing the frequency hopping signal itself,hopping frequencies can be estimated through a small number of measurements by the compressive sampling algorithm. Simulation results have proved that the proposed method is adequate to the environments in which the signal-to-noise ratio is higher than -2dB. Meanwhile, compared with other traditional methods, the proposed algorithm greatly reduces the amount of data, the computational complexity, and the identification time.