非均匀频率密度多载波新型雷达信号

在高超声速目标搜索应用中,要求雷达发射信号具有高分辨、低截获、高多普勒容限等特性。本文针对OFDM信号多普勒容限低的缺点,提出了一种非均匀频率密度多载波雷达信号以及基于NLFM信号频谱窗函数的子载波频率设计方法;采取理论分析及数值仿真方法,推导、计算了该信号的频谱特性及模糊函数特性,并与典型OFDM信号的有关特性进行了对比,得出结论:新信号具有多普勒容限大、无距离—多普勒耦合、带外衰减快以及时延自相关函数旁瓣低等优点,适合于宽带高分辨雷达对高速运动目标的搜索与检测。      

频谱细化及频谱校正技术在激光多普勒测速仪中的应用

提出了对多普勒信号先进行频谱细化,再进行频谱校正的方法,阐述了几种常见的离散频谱细化和频谱校正算法的基本原理,并运用它们对不同频率的理想正弦信号和实测的多普勒信号进行谱仿真和实测研究。理论分析和实验结果表明:频谱细化算法中Goertzel细化算法所需的运算量最少,计算速度最快;频谱校正算法中比值校正算法校正公式简单,运算量少,且校正精度较高;频谱细化和频谱校正技术大大提高了频谱分辨率,将其运用于频谱分析型激光多普勒测速仪中切实可行。     

感知空闲频谱的多普勒效应估计算法

在认知无线电的空闲频段二次利用中,针对感知用户通信可能引起的多普勒效应对临近信道带来的干扰的问题,提出了一种基于多普勒频谱扩展程度量化的实时计算方法。首先利用平方根升余弦函数使训练码频谱限定为特定带宽,并将感知空闲频谱划分为基带频段和保护频段,其次将保护频段划分为多个保护频段子区间,分别计算各个保护频段子区间的信号功率,最后累加信号功率不为零的保护频段子区间,即为整个信号的频谱扩展程度。文中方法同时也满足了对空闲频段实时检测的要求。仿真验证了在不同移动速度条件下,基于保护频段子区间的信号谱估计来计算多普勒频谱扩展的程度。     

基于混合编程的高精度激光多普勒信号处理技术

针对激光多普勒信号中存在较大噪声干扰的实际情况,为了抑制这些噪声干扰,提高激光多普勒测速仪的测量精度,提出了对激光多普勒信号进行最小均方差(LMS)自适应滤波后作快速傅里叶变换(FFT),基于混合编程思想对所得到的频谱,先进行频谱细化,再进行频谱校正的信号处理方法,并对理想正弦信号和实测多普勒信号分别进行仿真计算和实验研究。仿真和实验结果表明：LMS自适应滤波技术可以有效抑制激光多普勒测量中的多频率噪声的干扰,此技术能够适应于很宽的信噪比范围,大大提高多普勒信号的信噪比;频谱细化技术可以提高激光多普勒信号的频谱分辨率,频谱校正技术可以准确地校正多普勒频率,使校正后的频率更加接近于真实值;信号处理精度比直接进行FFT提高2~3倍。     

一种QAM信号多普勒参数盲估计方法

在卫星移动通信中,卫星相对地面接收站的高速运动导致接收信号存在时变多普勒频率,给正交幅度调制(QAM)信号的载波同步带来了极大困难.现有的多普勒参数估计方法多利用导频等先验信息,适用于移相键控(PSK)信号.但在估计多普勒频率变化率时假设多普勒频率较小,不符合实际情况,且现有方法无法估计较大的多普勒频率,另外在非协作通信下先验信息难以获得.对此,本文提出了一种针对高阶QAM信号的多普勒参数盲估计方法.将信号盲去调制后,利用瞬时频率估计函数,可在较大的多普勒频率下估计出多普勒频率变化率;通过检测信号四倍频率处的循环频率,实现了多普勒频率盲估计;最后利用arg运算求出初相.详尽的Monte Carlo仿真分析了方法的估计性能,仿真结果表明,所提方法能有效实现QAM信号的多普勒参数盲估计.     

基于微多普勒特征的空中目标识别

分析了直升机目标回波信号的微多普勒频谱，基于直升机目标和固定翼飞机目标多普勒频谱的差别，提出了两种微多普勒特征用于识别直升机目标和固定翼飞机目标，其中一种利用了直升机回波信号正负多普勒频谱能量的不对称性，另一种模式特征利用了机身回波信号能量与旋翼回波信号能量的对比，使用仿真数据和试验测试录制的数据的计算结果表明该方法具有很好的识别效果。     

基于圆白卷积的主载波捕获算法

在基于统一载波体制的深空测控通信中,为了有效消除大调制度下的多普勒频偏,提出一种利用频谱对称性、基于圆自卷积的主载波摘获新算法。首先对已下变频的采样信号做FFT变换计算出信号频谱;然后利用圆自卷积法计算出频谱的对称点,即为主载波频率。仿真分析和FPGA验证表明,该算法能够实现各种调制度下的主载波捕获,解决了深空测控通信中大调制度下的多普勒频偏问题。     

对MATLAB实现数字信号的QPSK的频谱分析

调相是信号调制的一种,是用调制信号去控制载波信号角度(频率或相位)变化的一种信号变换方式,可以分为频率调制(FM)和相位调制(PM).信号经过角度调制后,频谱结构将发生变化,频谱分析是处理信号的重要步骤和必要的保证.利用MATLAB7.0语言编制脚本文件,对信号调用相应的函数进行各种调制,并且对其进行频谱分析.     

电离层不同传播模式信号多普勒频移的实验研究

介绍了试验采用的设备和工作参数.依据试验数据,统计分析了电离层不同传播模式信号的多普勒频移、射线距离、信号强度、能量频谱的距离展宽和频率展宽,给出了不同传播模式信号多普勒频移、射线距离和信号强度间的比较结果.最后通过分析电离层不同传播模式信号多普勒频移与射线距离间的变化关系,得到了对不同传播模式多普勒频移变化规律的一些新的认识.     

车载MTD搜索雷达多普勒频率补偿方法

车载MTD搜索雷达行进间工作时,车体运动产生的多普勒频率使地物杂波频谱偏离零频位置,导致在MTD处理时地物杂波抑制性能变差,降低了雷达在杂波背景下的目标检测能力。该方法通过计算车体运动在地物回波中产生的多普勒频率,把车体运动多普勒频率计算值与相参基准信号频率叠加,输出多普勒频率叠加后的相参基准信号到接收机。在接收机中,多普勒频率叠加后的相参基准信号与中频信号混频,输出多普勒频率补偿后的相参视频信号,从而解决了车体运动对MTD处理的影响。     

Modeling sound generation in stenosed coronary arteries

Acoustic measurements obtained from sensitive microphones placed on the chest are being used in a procedure to noninvasively diagnose coronary artery disease. Utilizing specially developed signal processing techniques, the spectral content of isolated diastolic heart sounds has been estimated and usually shows an increase in high-frequency components in patients with occlusive coronary arteries. In order to establish a theory for the origin of these spectral features, a sound source model has been developed which combines an incremental network model of the left coronary artery tree with a transfer function model describing arterial chamber resonant characteristics. The network model predicts flow in both normal and stenosed coronary arteries. From this flow information, the arterial chamber transfer function model predicts the development of acoustic signals from the chamber resonant characteristics. The transfer function of a segment of coronary artery demonstrates two resonance frequencies. These resonance frequencies depend upon the length and diameter of the chamber segment, as well as upon the distal hydraulic impedance loading the segment. The lower resonance frequency can be excited by the usual flow fluctuations (low frequency) in the coronary artery. In cases of stenosis, the wideband spectral characteristics of the turbulence produced by the stenosis excites both the low and high resonance frequencies. In a small sample of patients, the spectra obtained from isolated diastolic acoustic signals recorded by a chest microphone agree well with those predicted by this theory.     

Modern spectral analysis techniques for blood flow velocity andspectral measurements with pulsed Doppler ultrasound

Four spectral analysis techniques were applied to pulsed Doppler ultrasonic quadrature signals to compare the relative merits of each technique for estimation of flow velocity and Doppler spectra. The four techniques were 1) the fast Fourier transform method, 2) the maximum likelihood method, 3) the Burg autoregressive algorithm, and 4) the modified covariance approach to autoregressive modeling. Both simulated signals and signals obtained from an in vitro flow system were studied. Optimal parameter values (e.g., model orders) were determined for each method, and the effects of signal-to-noise ratio and signal bandwidth were investigated. The modern spectral analysis techniques were shown to be superior to Fourier techniques in most circumstances, provided the model order was chosen appropriately. Robustness considerations tended to recommend the maximum likelihood method for both velocity and spectral estimation. Despite the restrictions of steady laminar flow, the results provide important basic information concerning the applicability of modern spectral analysis techniques to Doppler ultrasonic evaluation of arterial disease.     

Wavelet analysis of oscillations in the peripheral bloodcirculation measured by laser Doppler technique

The wavelet transform technique, a time-frequency method with logarithmic frequency resolution, was used to analyze oscillations in human peripheral blood flow measured by laser Doppler flowmetry. The oscillations extended over a wide frequency scale and their periods varied in time. Within the frequency range studied, 0.0095-1.6 Hz, five characteristic oscillations were revealed, arising from both local and central regulatory mechanisms. After the insertion of endothelium-dependent and endothelium-independent vasodilators the spectra of blood flow markedly differed in the frequency interval 0.0095-0.02 Hz. In this way it was demonstrated that endothelial activity is a rhythmic process that contributes to oscillations in blood flow with a characteristic frequency of around 0.01 Hz. The study illustrates the potential of laser Doppler flowmetry combined with dynamical systems analysis for studies of both the micro- and macroscopic mechanisms of blood flow regulation in vivo.     

基于RELAX的气象雷达回波参数化谱矩估计方法

气象雷达回波的功率、平均频率和谱宽等谱矩参数与气象目标的类型密切相关,如何准确估计一直是关注的问题。地杂波也是气象雷达面临的严重干扰。气象目标回波和地杂波的频谱呈现高斯谱的特征,其参数化模型可以利用来估计这些谱矩参数。提出了拟合信号功率谱的参数化谱矩估计方法,并采用RELAX的思想进行多个高斯谱信号混合时的谱矩参数估计。最后利用仿真气象雷达信号进行了实验和性能分析,实验结果表明提出的方法能准确估计出高斯功率谱的谱矩参数,且具有较高的分辨率。与脉冲对法相比可用于估计多个高斯谱混合的情况（比如地杂波和气象回波叠加在一起时）,与最大似然法相比降低了运算量。      

Differences in the power structures of Fourier transform andautoregressive spectral estimates of narrow-band Doppler signals

There is considerable interest in the application of autoregressive (AR) spectral analysis to ultrasonic Doppler signals. Sonograms produced using this technique are, however, very different from those produced using classic Fourier transform methods. Simulations have shown that the heights of the peaks in the AR spectra of narrow-band signals are not necessarily proportional to signal power, and should be used with caution in the context of Doppler signal processing     

Performance of a Discrete Spectral Peak Frequency Estimator for Doppler Wind Velocity Measurements

A frequency estimator formed from the peak of a discrete power spectrum is examined. Expressions to compute the performance of the estimator as a function of input signal bandwidth and signal-to-noise ratio are developed and used to study the estimator's capability to measure signal mean frequencies for remote Doppler measurement of atmospheric winds. Performance comparisons with the widely used complex-covariance estimator, based on simulations, show that frequency estimates formed from the spectral peak tend to have larger variance, except in the case of narrow-band input signals where the estimate standard deviation approaches that of the complex-covariance estimator.     

Nonstationarity broadening reduction in pulsed Doppler spectrummeasurements using time-frequency estimators

The spectral width of Doppler signals is used as measure of lesion-induced flow disturbance. Its estimation accuracy is compromised using the conventional short-term Fourier transform (STFT) since this method implicitly assumes signal stationarity during the signal window while the Doppler signals from arteries are markedly nonstationary. The Wigner-Ville (WVD), Choi-Williams (CWD) and Bessel distributions (BD), specifically designed for nonstationary signals, have been optimized for spectral width estimation accuracy and compared to the STFT under different signal to noise ratios using simulated Doppler signals of known time-frequency characteristics. The optimum parameter values for each method were determined as a Hanning window duration of 10 ms for the STFT, 40 ms for the WVD and CWD and 20 ms for the BD and dimensionless time-frequency smoothing constant values of five in the CWD and two in the BD. Thresholding was used to reduce the effect of cross terms and side lobes in the WVD and BD. With no added noise the WVD gave the lowest estimation error followed by the CWD. At signal-to-noise ratios (SNRs) of 10 dB and 20 dB the CWD and BD had similar errors and were markedly better than the other estimators. Overall the CWD gave the best performance     

Statistical study of the spectral broadening of skywave signalsbackscattered by the sea surface: application to RMS wave heightmeasurement with a skywave radar

HF skywave signals backscattered by the sea surface are studied on a large set of data (more than 30 h of 64 independent signals) to identify the sources of the broadening of the first-order spectral line. Using high-quality signals reflected by sporadic E ionospheric layers, the natural broadening due to sea-scattering effects has been scaled to about 3/100 Hz. When the signals propagate via F layer, the total broadening due to ionospheric effects is similar in magnitude and can be attributed to two causes. The first, due to frequency modulation effects, which can be identified and corrected, scales on average to 1/100 Hz. The second, called unresolved ionospheric effects, scales on average to 2/100 Hz and is probably due to the spatial variation of the ionospheric Doppler within the ionospheric control volume. Since they are greatly variable with time and space, the influence of these unresolved ionospheric effects can be reduced by sorting spectra, according to the value of the equivalent spectral width, before averaging. Using such sorting and correcting the signals for the ionospheric frequency modulation, 70% of the considered set of data are usable to measure the root mean square (RMS) wave height     

Analyzing Chaotic Spectra of DC–DC Converters Using the Prony Method

When dc-dc converters operate in chaotic modes, they can generate spread spectra, which are useful for reducing the electromagnetic interference (EMI). Conventionally, the Fast Fourier Transform (FFT) is used to analyze the spectra. However, it is not applicable to the inner-harmonics, the nonintegral multiples of the fundamental frequency, which is a prominent feature of chaotic signals. In this brief, the Prony method is suggested for chaotic spectral estimation of dc-dc converters. Numerical simulations show its advantages over the traditional FFT     

The removal of wall components in Doppler ultrasound signals by using the empirical mode decomposition algorithm

Doppler ultrasound systems, used for the noninvasive detection of the vascular diseases, normally employ a high-pass filter (HPF) to remove the large, low-frequency components from the vessel wall from the blood flow signal. Unfortunately, the filter also removes the low-frequency Doppler signals arising from slow-moving blood. In this paper, we propose to use a novel technique, called the empirical mode decomposition (EMD), to remove the wall components from the mixed signals. The EMD is firstly to decompose a signal into a finite and usually small number of individual components named intrinsic mode functions (IMFs). Then a strategy based on the ratios between two adjacent values of the wall-to-blood signal ratio (WBSR) has been developed to automatically identify and remove the relevant IMFs that contribute to the wall components. This method is applied to process the simulated and clinical Doppler ultrasound signals. Compared with the results based on the traditional high-pass filter, the new approach obtains improved performance for wall components removal from the mixed signals effectively and objectively, and provides us with more accurate low blood flow.