Gauss linear frequency modulation wavelet transforms and its application to seismic phases identification

Based on the characteristics of gradual change style seismic signal onset which has more high frequency signal components but less magnitude, this paper selects Gauss linear frequency modulation wavelet as base function to study the change characteristics of Gauss linear frequency modulation wavelet transform with difference wavelet and signal parameters, analyzes the error origin of seismic phases identification on the basis of Gauss linear frequency modulation wavelet transform, puts forward a kind of new method identifying gradual change style seismic phases with background noise which is called fixed scale wavelet transform ratio, and presents application examples about simulation digital signal and actual seismic phases recording onsets identification.

Time-Frequency Bandwidth Product Estimation of Sinusoidal Non-Linear Chirp Keying Scheme

Sine Non-linear Chirp Keying(SNCK) is a kind of high-efficient modulation scheme, which provides a potential new beamforming method in communication and radar systems. It has been proved to have advantages in some parameter estimation issues over conventional modulation schemes. In this paper, a novel transform termed as Discrete Sinusoidal Frequency Modulation transform(DSFMT) is proposed. Then, the DSFMT of SNCK signal is deduced and classified into three types, based on which, the time-bandwidth product is estimated by the proposed algorithm. Simulation results show that the noise has a signifi cant impact on the localization of the peak value and the time-bandwidth product can be estimated by using local ratio values when.

基于Z变换和改进FRI的LFM信号参数估计方法研究

为了完成线性调频(linear frequency modulation,LFM)信号的稀疏采样,并利用稀疏数据对原始信号参数进行估计,本文提出了一种基于Z变换和改进有限新息率(finite rate of innovation,FRI)的LFM信号参数估计方法。以Z变换理论为基础,设计了一种数学模型,一旦信号能够表达成该数学模型的结构形式,就能通过Z变换和零化滤波器的方法估计信号参数。然后,利用了自相关延迟的FRI结构对LFM信号采样,该结构不仅完成了LFM信号的稀疏采样,而且稀疏采样结果能够与数学模型结构相符。在理论上通过数学论证的方式证明了所提方法能够用于获取LFM信号参数信息,并通过仿真和实测数据验证了所提方法的有效性,理论和实验结果表明该方法只需要4个采样点就能实现对LFM信号的参数估计,并且实验中的参数估计误差均在3%以内,极大的提高有限新息率采样的参数估计效率。

Generalized Parseval’s Theorem on Fractional Fourier Transform for Discrete Signals and Filtering of LFM Signals

This paper investigates the generalized Parseval’s theorem of fractional Fourier transform (FRFT) for concentrated data. Also, in the framework of multiple FRFT domains, Parseval’s theorem reduces to an inequality with lower and upper bounds associated with FRFT parameters, named as generalized Parseval’s theorem by us. These results theoretically provide potential valuable applications in filtering, and examples of filtering for LFM signals in FRFT domains are demonstrated to support the derived conclusions.

基于分数阶傅里叶滤波的数字信道化储频

现代战场环境电磁日趋密集和复杂,各类信号相互混迭,同时各种相参雷达采用脉冲压缩技术以及相参处理方法,抗噪声和抗干扰能力大大增强,特别是采用线性调频(LFM)信号满足了雷达大威力、低截获的功能设计需求,抗干扰能力也得到提高。常规的数字储频(DRFM)采用宽带采集,在数字上对宽带信号进行调频、叠加等调制处理,在瞬时带宽内调制样式、参数是相同的,此处理方式导致瞬时带宽内多信号时,无法针对性施加不同的调制样式,以致干扰粗放、不够精确。为实现精确、有效的干扰相参脉冲压缩雷达,文中提出了采用频域子带处理与分数阶傅里叶滤波的数字信道化干扰设计,增强LFM信号去噪能力,通过DRFM技术形成假目标干扰信号,实施有效干扰。

基于线性调频连续波的合作式通信辐射源测距

针对加速运动目标参数估计中,离散多项式变换方法无法进行非整数估计的问题,本文提出基于瑞夫算法的离散多项式变换法和基于Chirp-Z变换的离散多项式变换法2种新型离散多项式变换算法,对加速运动目标速度和加速度进行估计,并对2种算法的估计误差和计算量进行了分析比较。结果表明:2种算法在信噪比-20 dB时均方误差开始接近克拉美罗界。基于瑞夫算法的离散多项式变换法与3次迭代基于Chirp-Z变换的离散多项式变换法均可在较低信噪比下可实现任意频率的有效估计且性能接近,二者均可实现低信噪比下速度、加速度的有效估计,但基于瑞夫算法的离散多项式变换法计算量远小于3次迭代基于Chirp-Z变换的离散多项式变换法。

Chirp-Z变换谱分析压制地震记录单频干扰

以往压制地震记录中的单频干扰有许多成功的方法,如频率域陷波法及时间域拟合法,其中以时间域拟合法压制强能量单频干扰最有效。但是拟合法通常采用基于频率扫描法搜寻单频波频率的方式,比较耗时,不能满足当前日益增长的高覆盖、高密度地震勘探数据处理的需要。本文提出应用基于Chirp-Z变换的高精度谱分析技术估计单频波的频率,不仅提高了计算效率,而且在压制单频干扰的同时有效保护了在单频干扰频率附近的有效信号。

线性调频变Z换在钢琴基音检测中的应用

首先分析了钢琴的基音检测要求和线性调频变换的性质,并将其用到基音检测中去,使检测的准确度、可靠性、抗干扰性、实时Z性、稳定性均达到了工厂的要求,大大降低了工人的劳动强度,提高了工厂的生产效率,使产品的质量更加稳定、可靠。

基于chirp-z变换的斜视FMCW-SAR非线性尺度变换算法

该文针对调频连续波合成孔径雷达(Frequency Modulated Continuous Wave Synthetic Aperture Radar,FMCW-SAR)在斜视模式下聚焦精度降低的问题,提出一种非线性尺度变换chirp-z成像算法。该算法利用回波信号在多普勒域中距离向的非线性特性,通过引入一个非线性调频信号对回波信号进行基于chirp-z的非线性尺度变换,降低距离压缩和距离徙动校正的误差,提高雷达图像分辨率。采用该成像算法对点目标模拟回波的成像结果与原始chirp-z算法相比,距离向分辨率和图像对比度得到提高,方位向分辨率保持不变。

脉冲噪声下基于CNN-FRFT的线性调频信号参数估计方法

由于脉冲噪声破坏了线性调频(LFM)信号的分数谱特征,使得基于分数谱特征的参数估计方法无法有效估计参数。针对这个问题,提出一种脉冲噪声环境下基于CNN-FRFT的LFM信号参数估计方法。首先,利用α稳定分布拟合随机脉冲噪声,构建加性含噪信号,输入卷积神经网络(CNN)进行训练和测试;其次,利用训练好的CNN模型对信号进行去噪,并验证模型的去噪能力和泛化能力;最后,利用分数阶傅里叶变换(FRFT)建立去噪信号的分数谱,通过峰值点位置来估计LFM信号的参数。实验结果表明,相比于传统的基于非线性函数的方法,该方法在强脉冲噪声环境下具有更好的精度和噪声鲁棒性,CNN的应用使其具有更强的泛化能力,在实测脉冲噪声下仍可以准确估计参数。

基于FRFT的低信噪比LFM信号参数快速估计算法

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。

基于Chirp_Z算法的雷达高度表研究

LFMCW雷达高度表通常采用FFT计算出回波的中频距离谱,但由于FFT的"栅栏效应",使得雷达高度表在低高度下测量的相对误差较大。为此本文在FFT的基础上采用Chirp_Z算法对其细化,给出了Chirp_Z变换在某LFMCW雷达高度表信号处理系统中DSP实现,通过采集实验系统中的实测数据,并与FFT算法进行比较,验证了该算法的可行性和高效性。

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 he 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.

Wigner-Hough transform based on slice's entropy and its application to multi-LFM signal detection

To enhance the capacity of the radar-reconnaissance interception receiver recognizing linear frequency modulated (LFM) at a low signal-noise ratio, this paper presents WignerHough transform (WHT) of the LFM signal and its corresponding characteristics, derives the probability density functions of the LFM signal and Gaussian white noise within WHT based on entropy (WHTE), dimension under different assumptions and puts forward a WHT algorithm based on entropy of slice to improve the capacity of detecting the LFM signal. Entropy of the WHT domain slice is adopted to assess the information size of polar radius or angle slice, which is converted into the weight factor to weight every slice. Double-deck weight is used to weaken the influences of noise and disturbance terms and WHTE treatment and signal detection procedure are also summarized. The rationality of the algorithm is demonstrated through theoretical analysis and formula derivation, the efficiency of the algorithm is verified by simulation comparison between WHT, fractional Fourier transform and periodic WHT, and it is highlighted that the WHTE algorithm has better detection accuracy and range of application against strong noise background.

Combining Radon-ambiguity transform with second-order difference to improve detection probability of LFM signals in low SNR

The Radon-ambiguity transform （RAT）, although efficient for detecting the linear frequency modulated signals （LFMs）, is troubled by the energy accumulation of noise in low signal-to-noise ratio （SNR）. A secondorder difference （SOD） method is proposed to treat with this problem. In the SOD method, the optimal search step and difference step are derived from the LFM rate resolution formula. The sharpness of the peaks of RAT is measured by curvature, and the sharpness, but not the magnitude of the peaks, is used to detect the LFMs. The SOD method removes the noise energy accumulation and reserves the drastically changing components integrally; thus, it improves the detection probability of LFMs in low SNR. The expected performance of the new method is verified by 100 Monte Carlo simulations.

Transformer网络在雷达辐射源识别中的应用

由于雷达辐射源信号在时序上具有强相关性,针对卷积神经网络难以提取信号的时序逻辑相关性特征的缺点,本文提出了基于Transformer网络的雷达辐射源个体识别的方法。该方法首先以3台信号发生器模拟雷达辐射源信号,同时采集数据并建立数据库;然后对原始信号提取相位特征以及包络特征;最后采用基于注意力机制的Transformer网络对信号进行进一步的特征提取并分类。实验结果表明,该算法对于包络特征以及相位特征敏感度不同,同时数据样本长度对于识别效果会产生影响,最终结合相位特征的网络模型在信噪比为15 dB时识别率可以达到98.9%。

基于LVD与Zoom-FRFT的多分量LFM信号参数估计

针对基于分数阶傅里叶变换(FRFT)的多分量线性调频信号(MLFM)参数估计方法中计算量大、估算精度低等问题,本文提出了一种基于吕分布(LVD)与高分辨分数阶傅里叶变换(Zoom-FRFT)的参数估计方法。首先,对MLFM信号进行LVD,检测存在的分量个数,对各分量参数粗略估计,利用粗略调频斜率代入FRFT的参数估计公式,反向计算出FRFT的粗略变换阶次。然后,以粗略变换阶次为中心限定范围,设置精度,连续进行FRFT,从而提取峰值的坐标即精确变换阶次与粗略FRFT域坐标。最后,在精确变换阶次下,以粗略FRFT域坐标为中心限定区间,进行Zoom-FRFT,从而提取精确FRFT域坐标,对分量的参数进行精估计。仿真结果表明,该方法可以有效地对MLFM信号进行参数估计,并可以根据实际需要选择变换阶次的搜索范围与精度、FRFT域的细化倍数;与传统方法相比,本方法同时提高了参数估计精度与计算效率。

基于HHT时频分析的水声信号特性提取与建模

为了完成对实测水下冲击信号的建模,充分提取信号声学特性是非常有必要的。本文以水池实测信号为研究对象,采用不同分析方法处理信号,最终发现希尔伯特黄变换(HHT)时频分析方法优势明显,在HHT时频谱图上可以看到非常清晰的时间、频率分布信息。在此基础上,使用多段线性调频(LFM)信号模拟实测水下冲击信号。比较实测信号与建模信号的HHT谱图可知,建模信号的频谱走势与实测信号相同,具有与实测水声信号非常相似的时频特性,验证了HHT时频分析的优势与建模效果。

基于FRFT的单基地MIMO雷达稳健波束形成算法

以单基地多输入多输出(multiple input multiple output,MIMO)雷达系统为研究对象,针对线性调频(linear frequency modulation,LFM)形式的正交频分复用(orthogonal frequency division multiplexing,OFDM)信号,提出了一种新的稳健自适应波束形成算法。所提算法首先利用LFM信号的特性,对匹配滤波后的雷达回波信号进行分数阶傅里叶变换(fractional Fourier transform,FRFT),经化简得到峰值点作为阵列的观测值。而后,利用观测值构建接收信号的协方差矩阵,并使用Capon谱估计方法重构干扰加噪声数据协方差矩阵。最后,通过求解优化问题估计实际导向矢量,从而得到阵列的最优权值。通过计算机仿真实验,验证了所提算法的有效性。