用一种新的空时导向矢量联合估计CDMA信号波达方向与多径时延

本文针对CDMA系统提出了一种不需要训练信号而直接对接收的正常通信信号进行处理,实现感兴趣用户的波达方向(DOA)与多径时延联合估计的新方法.该方法是一种基于空时二维的MUSIC方法,首先建立了一种新的数据结构,并对其形成的相关矩阵进行特征分解,然后采用构造的新导向矢量对特征空间进行搜索.这种方法克服了要求接收信号数小于阵元数的局限,能有效估计时延不同、波达方向相差很小的多径信号的参数.

基于麦克风阵列的相容时延矢量声源定位方法

时延估计是常用的声源定位方法,传统的算法将定位分为两个步骤,即先估计麦克风阵列中每一对基元的接收信号时延,然后根据这些时延用几何的方法确定声源的位置。在低信噪比下,一对麦克风的时延估计误差较大,导致定位误差较大。相容时延矢量估计算法将两步合为一步,没有逐对估计时延,而是构造一个目标函数,通过搜索得到声源的位置。仿真结果表明,在低信噪比下,只需要较短的数据,该算法仍可得到较高的定位精度。

基于空时特征矢量的空时多用户检测

文章提出了一种新的空时多用户检测方法,该方法有效地结合了空间与时间处理。在求充分统计量中,定义了一种维数较高的空时特征矢量,它包含了各接收阵元阵列响应与扩频序列的联合信息。在求出的充分统计量中包含了各接收阵元之间的信息,在抑制干扰过程中采用了更有效的正交空间投影算法。在DS-CDMA异步多径信道下,仿真结果证明,该方法能有效地抑制多址干扰与多径干扰。

级联型逆变器的新型简化多电平空间矢量调制方法

传统多电平空间矢量调制(space vector modulation,SVM)方法需要大量的矢量选择等复杂运算,级联数目较高时,算法变得异常复杂而难以实现。该文借鉴载波移相调制的思想,提出一种新颖的基于两电平SVM的简化多电平SVM方法。将各级H桥逆变器施加相同幅值和相位的电压矢量,而将各自的电压矢量更新时间相互错开,进而形成相应的多电平输出电压波形。每个采样周期只需依据两电平SVM算法计算一单元的主、辅电压矢量及其作用时间,计算量与级联数目无关,进而显著简化了算法难度,并增强了可扩展性。三单元情况的仿真和实验结果证明了所提出方法的正确性和可行性。

基于空时导向约束的天基雷达离散旁瓣杂波判别方法

由于天基雷达覆盖范围广,大量强离散杂波(小型岛礁、陆地铁塔等)会从天线旁瓣进入雷达系统,其多普勒特征与目标相同,极易造成虚警。针对以上问题,该文提出基于空时导向约束的天基雷达离散旁瓣杂波判别方法,该方法首先选取空时自适应处理(STAP)杂波抑制后检测到的潜在“目标”(包含真实目标与离散旁瓣杂波)距离多普勒单元及其附近单元;然后根据杂波多普勒频率与空间角度的耦合关系获得各杂波单元对应的空时导向矢量;最后利用获得新的导向矢量构成的滤波器再次对“目标”距离多普勒单元及其附近单元进行滤波处理,此时真实目标信杂噪比会大幅度降低,而离散旁瓣杂波信杂噪比变化不大,从而实现离散旁瓣杂波的判别。理论分析及机载实测数据处理证明该方法具有良好的稳健性和可靠性。

级联型逆变器的新型多电平SVPWM研究

多电平SVPWM的研究,目前主要集中在错时采样SVPWM。错时采样SVPWM算法复杂,实时性差。对该SVPWM调制技术进行分析,应用一种能显著降低算法复杂度的新型多电平SVPWM技术———单元矢量延时叠加SVPWM技术。该算法显著降低了算法复杂度,且实时性极好。通过Matlab仿真和实验研究,验证了方案的可行性和实用价值。这种算法在级联多电平领域有广阔的应用前景。

级联型逆变器多电平PWM控制及仿真研究

通用的级联型H桥多电平高压逆变器一般采用载波移相SPWM和错时采样SVPWM技术。基于对多电平PWM控制仿真模型的构建及分析,针对这两种技术共有的占用系统资源多和实时性差等缺点,提出一种新型简化多电平PWM技术——单元矢量延时叠加PWM(Overlap time staggered PWM,OTS-PWM)技术,并总结出相应的PWM调制规律。分别对OTS-SPWM和OTS-SVPWM调制技术的仿真实现,表明了本方法能够显著降低了运算复杂度,且实时性好,并验证OTS-PWM技术的有效性和通用性,及其在级联多电平PWM领域的广阔应用前景。

基于级联型逆变器的新型PWM技术研究

级联型H桥多电平逆变器的PWM调制技术一般采用载波移相SPWM技术和错时采样SVPWM。对这两种PWM调制技术进行分析,应用一种新型简化多电平PWM技术,即单元矢量延时叠加PWM(Overlap time staggeredPWM,OTS-PWM)技术于级联型H桥多电平逆变器。通过对OTS-SPWM和OTS-SVPWM调制技术的的仿真研究,总结了相应的调制规则。最后通过对OTS-SVPWM技术进行实验研究,验证了方案的实用价值。

对STAP处理器的投散射式伪杂波干扰技术

具有空时自适应处理技术(STAP)的机载雷达从空时二维联合域处理信号,而传统干扰方法因信号维度单一性很难产生有效干扰效果。文中针对STAP处理器抗干扰特性,提出一种具有空时二维特性的投散射式伪杂波干扰新技术,根据多普勒频率对方位的依从关系,向地面投射干扰信号,利用地面散射特性产生与地杂波特性相似的伪杂波干扰信号。分析了该干扰信号的空时矢量模型,研究了干扰信号二维功率谱的轨迹可控性问题。该干扰信号在空时二维空间上呈现不与杂波轨迹重合的刀背式分布,多普勒轨迹可控,能控制干扰信号的二维功率谱始终覆盖在被保护目标上。仿真实验结果显示:处理器改善因子降低,杂波谱畸变,证明了该干扰方法的有效性。

Elastic reverse-time migration based on amplitude-preserving P- and S-wave separation

Imaging the PP- and PS-wave for the elastic vector wave reverse-time migration requires separating the P- and S-waves during the wave field extrapolation. The amplitude and phase of the P- and S-waves are distorted when divergence and curl operators are used to separate the P- and S-waves. We present a P- and S-wave amplitude-preserving separation algorithm for the elastic wavefield extrapolation. First, we add the P-wave pressure and P-wave vibration velocity equation to the conventional elastic wave equation to decompose the P- and S-wave vectors. Then, we synthesize the scalar P- and S-wave from the vector P- and S-wave to obtain the scalar P- and S-wave. The amplitude-preserved separated P- and S-waves are imaged based on the vector wave reverse-time migration （RTM）. This method ensures that the amplitude and phase of the separated P- and S-wave remain unchanged compared with the divergence and curl operators. In addition, after decomposition, the P-wave pressure and vibration velocity can be used to suppress the interlayer reflection noise and to correct the S-wave polarity. This improves the image quality of P- and S-wave in multicomponent seismic data and the true-amplitude elastic reverse time migration used in prestack inversion.

Extraction of amplitude-preserving angle gathers based on vector wavefield reverse-time migration

Angle-domain common-image gathers （ADCIGs） transformed from the shot- domain common-offset gathers are input to migration velocity analysis （MVA） and prestack inversion. ADCIGs are non-illusion prestack inversion gathers, and thus, accurate. We studied the extraction of elastic-wave ADCIGs based on amplitude-preserving elastic-wave reverse- time migration for calculating the incidence angle of P- and S-waves at each image point and for different source locations. The P- and S-waves share the same incident angle, namely the incident angle of the source P-waves. The angle of incidence of the source P-wavefield was the difference between the source P-wave propagation angle and the reflector dips. The propagation angle of the source P-waves was obtained from the polarization vector of the decomposed P-waves. The reflectors＇ normal direction angle was obtained using the complex wavenumber of the stacked reverse-time migration （RTM） images. The ADCIGs of P- and S-waves were obtained by rearranging the common-shot migration gathers based on the incident angle. We used a horizontally layered model, the graben medium model, and part of the Marmousi-II elastic model and field data to test the proposed algorithm. The results suggested that the proposed method can efficiently extract the P- and S-wave ADCIGs of the elastic-wave reverse-time migration, the P- and S-wave incident angle, and the angle-gather amplitude fidelity, and improve the MVA and prestack inversion.

Surface wave attenuation based polarization attributes in time-frequency domain for multicomponent seismic data

In the paper, we propose a surface wave suppression method in time-frequency domain based on the wavelet transform, considering the characteristic difference of polarization attributes, amplitude energy and apparent velocity between the effective signals and strong surface waves. First, we use the proposed method to obtain time-frequency spectra of seismic signals by using the wavelet transform and calculate the instantaneous polarizability at each point based on instantaneous polarization analysis. Then, we separate the surface wave area from the signal area based on the surface-wave apparent velocity and the average energy of the signal. Finally, we combine the polarizability, energy, and frequency characteristic to identify and suppress the signal noise. Model and field data are used to test the proposed filtering method.

Nonlinear Time Series Prediction Using LS-SVM with Chaotic Mutation Evolutionary Programming for Parameter Optimization

Nonlinear time series prediction is studied by using an improved least squares support vector machine （LSSVM） regression based on chaotic mutation evolutionary programming （CMEP） approach for parameter optimization. We analyze how the prediction error varies with different parameters （σ, γ） in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.

Extraction of P-and S-wave angle-domain common-image gathers based on first-order velocity-dilatation-rotation equations

Accuracy of angle-domain common-image gathers(ADCIGs)is the key to multiwave AVA inversion and migration velocity analysis,and of which Poynting vectors of pure P-and S-wave are the decisive factors in obtaining multi-component seismic data ADCIGs.A Poynting vector can be obtained from conventional velocity-stress elastic wave equations,but it focused on the propagation direction of mixed P-and S-wave fields,and neither on the propagation direction of the P-wave nor the direction of the S-wave.The Poynting vectors of pure P-or pure S-wave can be calculated from first-order velocity-dilatation-rotation equations.This study presents a method of extracting ADCIGs based on first order velocitydilatation-rotation elastic wave equations reverse-time migration algorithm.The method is as follows:calculating the pure P-wave Poynting vector of source and receiver wavefields by multiplication of P-wave particle-velocity vector and dilatation scalar,calculating the pure S-wave Poynting vector by vector multiplying S-wave particle-velocity vector and rotation vector,selecting the Poynting vector at the time of maximum P-wave energy of source wavefield as the propagation direction of incident P-wave,and obtaining the reflected P-wave(or converted S-wave)propagation direction of the receiver wavefield by the Poynting vector at the time of maximum P-(S-)wave energy in each grid point.Then,the P-wave incident angle is computed by the two propagation directions.Thus,the P-and S-wave ADGICs can obtained Numerical tests show that the proposed method can accurately compute the propagation direction and incident angle of the source and receiver wavefields,thereby achieving high-precision extraction of P-and S-wave ADGICs.

Discussion About Nonlinear Time Series Prediction Using Least Squares Support Vector Machine

The least squares support vector machine (LS-SVM) is used to study the nonlinear time series prediction. First, the parameter gamma and multi-step prediction capabilities of the LS-SVM network are discussed. Then we employ clustering method in the model to prune the number of the support values.. The learning rate and the capabilities of filtering noise for LS-SVM are all greatly improved.

Compensation of Dead-Time Effect of Speed Sensorless Vector Control System

The key of speed sensorless vector control system lies in the accurate orientation of magnetic field. In some field-oriented algorithms, the integrator of observers and the dead-time effect bring in system errors during the estimation of field position. In this paper, a saturated feedback integrator is used, and the dead-time effect is compen- sated by current positive feedback. Experiments were carried out on the hardware platform of MCK2407, with chip TMS320LF2407 from TI Company. The results show that the prooosed method is simole and effective, and the accuracy of field position is improved.

A NOVEL METHOD FOR CALCULATING VERTICAL VELOCITY:A RELATIONSHIP BETWEEN HORIZONTAL VORTICITY AND VERTICAL MOVEMENT

The present work provides a novel method for calculating vertical velocity based on continuity equations in a pressure coordinate system.The method overcomes the disadvantage of accumulation of calculating errors of horizontal divergence in current kinematics methods during the integration for calculating vertical velocity,and consequently avoids its subsequent correction.In addition,through modifications of the continuity equations,it shows that the vorticity of the vertical shear vector(VVSV) is proportional to-ω,the vertical velocity in p coordinates.Furthermore,if the change of ω in the horizontal direction is neglected,the vorticity of the horizontal vorticity vector is proportional to-ω.When ω is under a fluctuating state in the vertical direction,the updraft occurs when the vector of horizontal vorticity rotates counterclockwise;the downdraft occurs when rotating clockwise.The validation result indicates that the present method is generally better than the vertical velocity calculated by the ω equation using the wet Q-vector divergence as a forcing term,and the vertical velocity calculated by utilizing the kinematics method is followed by the O'Brien method for correction.The plus-minus sign of the vertical velocity obtained with this method is not correlated with the intensity of d BZ,but the absolute error increases when d BZ is >=40.This method demonstrates that it is a good reflection of the direction of the vertical velocity.

Space and Temporal Distribution Analysis of Interictal Spike in Epilepsy

Stereo-electroencephalography （SEEG） is the main investigation method for pre-surgical evaluation of patients suffering from drug-resistant partial epilepsy. SEEG signals reflect two types of paroxysmal activity： ictal activity and interictal activity or interictal spikes （IS）. The relationship between IS and ictal activity is an essential and recurrent question in epiletology. In this paper, we present a distributed and parallel architecture for space and temporal distribution analysis of IS, based on a distributed and collaborative methodology. The proposed approach exploits the SEEG data using vector analysis of the corresponding signals among multi-agents system. The objective is to present a new method to analyze and classify IS during wakefulness （W）, light sleep （LS） and deep sleep （DS） stages. Temporal and spatial relationships between IS and seizure onset zone are compared during wakefulness, light sleep and deep sleep. Results show that space and temporal distribution for real data are not random but correlated.

Interpretation of sea surface wind interannual vector EOFs over the China seas

Using interpolation and averaging methods, we analyzed the sea surface wind data obtained from December 1992 to November 2008 by the scatterometers ERS-1, ERS-2, and QuikSCAT in the area of 2°N-39 °N, 105°E-130°E, and we reported the monthly mean distributions of the sea surface wind field. A vector empirical orthogonal function （VEOF） method was employed to study the data and three temporal and spatial patterns were obtained. The first interannual VEOF accounts for 26% of the interannual variance and displays the interannual variability of the East Asian monsoon. The second interannual VEOF accounts for 21% of the variance and reflects the response of China sea winds to E1 Nifio events. The temporal mode of VEOF-2 is in good agreement with the curve of the Nifio 3.4 index with a four-month lag. The spatial mode of VEOF-2 indicates that four months after an E1 Nifio event, the southwesterly anomalous winds over the northern South China Sea, the East China Sea, the Yellow Sea, and the Bohai Sea can weaken the prevailing winds in winter, and can strengthen the prevailing winds in summer. The third interannual VEOF accounts for 10% of the variance and also reflects the influence of the ENSO events to China Sea winds. The temporal mode of VEOF-3 is similar to the curve of the Southern Oscillation Index. The spatial mode of VEOF-3 shows that the northeasterly anomalous winds over the South China Sea and the southern part of the East China Sea can weaken the prevailing winds, and southwesterly anomalous winds over the northern part of the East China Sea, the Yellow Sea, and the Bohai Sea can strengthen the prevailing winds when E1 Nifio occurs in winter. If E1 Nifio happens in summer, the reverse is true.

Different Options Regarding Power Components in Electric Circuits

This paper describes two methods of representation of voltages and currents in electric circuits： in the vector form and in the shape of oscillations, represented as diagrams in the plane. The appropriate power components are discussed depending on the representation of voltages and currents. Special attention is paid to the instantaneous power peculiarities for diverse loads and non-sinusoidal conditions. A case study of power calculations in an electric circuit with a pluggable capacitor is presented. For these types of transient modes, the instantaneous power is represented in the form of active and reactive components. Calculation of active, reactive, and exchange powers for steady-state processes is presented.