Source time functions of the Gonghe，China earthquake retrieved from long－period digital waveform data using empirical Green＇s function technique

An earthquake of Ms= 6, 9 occurred at the Gonghe, Qinghai Province, China on April 26, 1990. Three larger aftershocks took place at the same region, Ms= 5. 0 on May 7, 1990, Ms= 6. 0 on Jan. 3, 1994 and Ms= 5. 7on Feb. 16, 1994. The long-period recordings of the main shock from China Digital Seismograph Network (CDSN) are deconvolved for the source time functions by the correspondent0 recordings of the three aftershocks asempirical Green's functions (EGFs). No matter which aftershock is taken as EGF, the relative source time functions (RSTFs) Obtained are nearly identical. The RSTFs suggest the Ms= 6. 9 event consists of at least two subevents with approximately equal size whose occurrence times are about 30 s apart, the first one has a duration of 12 s and a rise time of about 5 s, and the second one has a duration of 17 s and a rise time of about & s. COmParing the RSTFs obtained from P- and SH-phases respectively, we notice that those from SH-phases are a slightly more complex than those from p-phases, implying other finer subevents exist during the process of the main shock. It is interesting that the results from the EGF deconvolution of long-Period way form data are in good agreement with the results from the moment tensor inversion and from the EGF deconvolution of broadband waveform data. Additionally, the two larger aftershocks are deconvolved for their RSTFs. The deconvolution results show that the processes of the Ms= 6. 0 event on Jan. 3, 1994 and the Ms= 5. 7 event on Feb. 16,1994 are quite simple, both RSTFs are single impulses.The RSTFs of the Ms= 6. 9 main shock obtained from different stations are noticed to be azimuthally dependent, whose shapes are a slightly different with different stations. However, the RSTFs of the two smaller aftershocks are not azimuthally dependent. The integrations of RSTFs over the processes are quite close to each other, i. e., the scalar seismic moments estimated from different stations are in good agreement. Finally the scalar seismic moments of the three aftershocks are compared. The relative scalar seismic moment Of the three aftershocks deduced from the relative scalar seismic moments of the Ms=6. 9 main shock are very close to those inverted directly from the EGF deconvolution. The relative scalar seismic moment of the Ms =6. 9 main shock calculated using the three aftershocks as EGF are 22 (the Ms= 6. 0 aftershock being EGF), 26 (the Ms= 5. 7 aftershock being EGF) and 66 (the Ms= 5. 5 aftershock being EGF), respectively. Deducingfrom those results, the relative scalar sesimic moments of the Ms= 6. 0 to the Ms= 5. 7 events, the Ms= 6. 0 tothe Ms= 5. 5 events and the Ms= 5. 7 to the Ms= 5. 5 events are 1. 18, 3. 00 and 2. 54, respectively. The correspondent relative scalar seismic moments calculated directly from the waveform recordings are 1. 15, 3. 43, and 3. 05.

Arbitrary Waveforms Based on Front Panel of Agilent 33250A Function/Arbitrary Waveform Generator

Agilent 33200A family of function/arbitrary waveform generators are widely used in labs for creating arbitrary waveforms.Flexible applications of function/arbitrary waveform generator 33250A which is made by Agilent company are expatiated.There are three methods of transferring waveform data to arbitrary waveform generator 33250A,among which,the front panel method can produce a simple interface for arbitrary waveforms and is applicable to the composition of a small amount of linear waveform segment,and the progress of this method is explained in detail.This way is convenient and can be widely used,and it will offer some good guidance in library works.

Source time functions of the 1999, Jiji (Chi-Chi) earthquake from GDSN long period waveform data using aftershocks as empirical Green's functions

A large earthquake (Mw=7.6) occurred in Jiji (Chi-Chi), Taiwan, China on September 20, 1999, and was followed by many moderate-size shocks in the following days. Two of the largest aftershocks with the magnitudes of Mw=6.1 and Mw=6.2, respectively, were used as empirical Green's functions (EGFs) to obtain the source time functions (STFs) of the main shock from long-period waveform data of the Global Digital Seismograph Network (GDSN) including IRIS, GEOSCOPE and CDSN. For the Mw=6.1 aftershock of September 22, there were 97 pairs of phases clear enough from 78 recordings of 26 stations; for the Mw=6.2 aftershock of September 25, there were 81 pairs of phases clear enough from 72 recordings of 24 stations. For each station, 2 types of STFs were retrieved, which are called P-STF and S-STF due to being from P and S phases, respectively. Totally, 178 STF individuals were obtained for source-process analysis of the main shock. It was noticed that, in general, STFs from most of the stations had similarities except that those in special azimuths looked different or odd due to the mechanism difference between the main shock and the aftershocks; and in detail, the shapes of the STFs varied with azimuth. Both of them reflected the stability and reliability of the retrieved STFs. The comprehensive analysis of those STFs suggested that this event consisted of two sub-events, the total duration time was about 26 s, and on the average, the second event was about 7 s later than the first one, and the moment-rate amplitude of the first event was about 15% larger than that of the second one.

FAST COMPUTATION OF WIDEBAND RCS USING CHARACTERISTIC BASIS FUNCTION METHOD AND ASYMPTOTIC WAVEFORM EVALUATION TECHNIQUE

The Asymptotic Waveform Evaluation (AWE) technique is an extrapolation method that provides a reduced-order model of linear system and has already been successfully used to analyze wideband electromagnetic scattering problems. As the number of unknowns increases, the size of Method Of Moments (MOM) impedance matrix grows very rapidly, so it is a prohibitive task for the computation of wideband Radar Cross Section (RCS) from electrically large object or multi-objects using the traditional AWE technique that needs to solve directly matrix inversion. In this paper, an AWE technique based on the Characteristic Basis Function (CBF) method, which can reduce the matrix size to a manageable size for direct matrix inversion, is proposed to analyze electromagnetic scattering from multi-objects over a given frequency band. Numerical examples are presented to il-lustrate the computational accuracy and efficiency of the proposed method.

基于偏振复用调制的周期性光学任意波形生成方案

针对复杂波形生成的需求,提出了一种基于偏振复用调制的周期性光学任意波形信号生成方案。通过精心调控正交相移键控(QPSK)调制器的调制指数、射频偏移及偏置相移等关键参数,使得2个正交偏振态上的调制器能够分别输出傅里叶级数中的正弦和余弦谐波叠加形式的光强。当这些光强合束后,就能得到幅度和相位均可精确控制的函数波形,而且还具备可调谐函数波形信号输出的特性。仿真结果表明:当均方根误差小于等于0.05时,该方案可生成对称因子可调(20%~80%)斜坡波、占空比可调(30%~100%)三角波和半占空比可调(20%~80%)斜坡波3种典型波形,验证了该方案的可行性。

基于指数相位相关性目标函数的全波形反演

全波形反演(FWI)已成为获取浅地表高分辨率S波速度(VS)的有效方法。为了克服FWI在野外应用中的一些挑战,文中引入了一种基于指数相位相关性的目标函数,该函数不依赖于测量和模拟数据的振幅信息。文中采用伴随状态方法高效计算目标函数相对于模型的梯度,并分析了新目标函数的形状。使用受随机噪声污染的模拟数据,证明了该目标函数对随机噪声的鲁棒性。此外,使用在考古遗址上采集的地震数据作为基准数据集,测试了基于指数相位相关性的全波形反演方法在真实野外环境中的性能,同时还添加了随机噪声以进一步评估目标函数对噪声的鲁棒性。文中所得反演结果与该遗址已有的速度结构非常相似,并已通过独立的考古挖掘验证。因此,基于指数相位相关性目标函数的FWI具有在实际野外情况下显著提高浅地表成像准确性的潜力。

基于LabVIEW的数字滤波器性能研究

为了研究滤波器的滤波性能,采用LabVIEW设计了滤波器性能研究系统。通过LabVIEW中的波形生成函数输出幅值及频率可调的正弦波和白噪声2种信号,白噪声与正弦波叠加,通过滤波器输出正弦波信号,通过FFT输出正弦波的频谱特性。仿真结果表明:叠加有较小幅值噪声的正弦波信号通过一定的滤波器能够被不失真地滤波输出;当噪声的幅值较大时,滤波器输出的正弦波就会失真。调节滤波器的抽头数可以不失真的恢复出正弦波信号。所设计的系统界面直观、操作简单,可以应用于教学和科研。

基于改进VMD-WTFD算法的二次谐波光谱信号反演分析

采用变分模态分解和小波阈值调整函数(VMD-WTFD)算法在处理噪声时,信号波形恢复往往偏离标准的谐波信号,导致反演结果出现偏差。提出了一种改进VMD-WTFD算法,该算法采用新型阈值函数对VMD-WTFD算法进行改进,然后以此改进算法对二次谐波光谱信号进行反演分析。仿真与实验结果表明:与其它几种降噪算法相比,改进VMD-WTFD算法在不同调制度下反演出的原始信号的峰值、峰位和峰谷值更接近原始标准二次谐波光谱信号,去噪后的信噪比为17.545 dB,相关系数可达到0.9929;可以较清晰地反演出人体呼出气体中CO_(2)的二次谐波幅值。

基于分式二次规划的互模糊函数赋形方法

在开展认知雷达波形设计时,由于发射波形与接收滤波器的非匹配体制,互模糊函数赋形相比传统模糊函数赋形优化自由度更高。该文针对强杂波条件下微弱运动目标检测问题,以最大化信干噪比为优化准则,提出了一种联合发射相位编码序列与接收滤波器设计的互模糊函数赋形方法。在恒模约束下,优化问题被建模为二次分式规划形式;然后通过引入辅助变量,并利用共轭梯度法求解Stiefel流形空间上的最小化问题,非凸优化据此转化为恒模约束二次优化问题;通过交替循环和类幂迭代算法求得最优解。此外考虑到发射波形受硬件限制而难以实现严格恒模,该文构建了一种低峰均比约束二次优化问题模型,并利用最近邻向量法求得最优解。最后,不同参数下的仿真与实测数据实验表明,该文赋形方法相较于传统方法具有较高的信干噪比增益和收敛速度。

基于OPPERMANN序列扩频的雷达通信一体化波形设计

共享波形设计是雷达通信一体化系统最大化资源利用效率的关键。针对现有的一体化波形多址通信功能欠缺问题,设计了一种基于OPPERMANN序列扩频的雷达通信一体化波形。利用OPPERMANN序列对雷达脉冲信号进行加权,在子脉冲内调制多个下行链路用户的通信信号,并采用正交的OPPERMANN序列对不同用户的通信信号和雷达信号进行扩频,从而实现雷达与通信双重功能。理论分析和仿真实验表明,所设计的一体化波形使雷达和通信信号共享同一频带,不仅可以同时与多个下行链路的用户进行通信,还具有不同类型的模糊函数,可以满足雷达系统在目标探测和目标跟踪场景下的波形设计需求。

已知波形信号的时差频差估计方法研究与性能分析

借助深入分析和长期积累,非合作定位系统可以获得关于电视、广播、导航等电磁信号波形的丰富先验信息,对这些信息加以利用有望大幅提高对信号参数的估计精度。该文针对导航、通信等欺骗干扰源及非法用户的无源定位需求,在观测站与辐射源之间存在相对运动的场景下,围绕已知波形信号开展时差频差估计问题研究。首先,通过引入已知的信号波形信息对观测站接收数据进行建模,直观呈现了观测数据与不同观测站信号相对于原始信号时延、频移的关系。随后,充分利用入射信号波形已知这一有利条件,通过估计两个观测站各自的时延和频移,并对不同观测站上的估计结果进行差分,提出了一种针对已知波形信号的双站时差、频差估计方法。在此基础上,该文分析了已知波形信号时频差估计精度的理论下界,揭示了时频差估计精度受观测站接收信号幅度等因素的影响情况,并进一步分析了双站时频差估计精度与单通道时延、频移估计精度之间的关系。最后,借助仿真实验验证了论文所提出的时频差估计方法在不同环境中的参数估计性能,以及信号波形先验信息的利用给时频差参数估计精度带来的提升情况。仿真结果表明,在所设定的信号环境中,该文所提出的方法对低信噪比的适应能力比基于互模糊函数的传统方法增强了15 dB左右;当该方法的参数估计性能达到收敛之后,其时差频差估计精度与CRLB非常吻合。

太赫兹频段OFDM一体化波形的雷达探测性能分析

传统的正交频分复用(OFDM)信号在太赫兹通信系统中通常会面临峰均功率比(PAPR)过高的问题,严重降低功率放大器的效率,恶化太赫兹链路的非线性效应。恒模雷达-通信一体化波形可以抑制PAPR的影响。本文采用模糊函数作为评价标准,从距离和速度两方面分析和比较了太赫兹频段正交频分复用-16阶正交幅相调制-线调频(OFDM-16QAM-LFM)、正交频分复用-二进制相移键控-线调频(OFDM-BPSK-LFM)、正交频分复用-最小相移键控-线调频(OFDM-MSK-LFM)3种OFDM一体化波形的雷达探测性能。数值仿真结果表明,OFDM-16QAM-LFM波形在太赫兹频段的距离和速度探测性能良好,但PAPR过高;OFDM-BPSK-LFM、OFDM-MSK-LFM波形采用相位调制代替幅度-相位调制,保持恒定包络特性;OFDM-BPSK-LFM一体化波形的距离分辨力不会随着子载波数量增加而恶化,但速度分辨力随着子载波数量的增加而受到很大影响,不适宜用于高速运动状态下多目标的速度检测;OFDM-MSK-LFM波形可承载更多的子载波,适应复杂场景下的多载波雷达探测需求。本文方法为不同应用场景的一体化波形选择提供了参考。

Joint adaptive waveform and baseline range design for bistatic radar

The problems of joint adaptive waveform design and baseline range design for bistatic radar to maximize the practical radar resolution were considered.Distinguishing from the conventional ambiguity function(AF)-based resolution which is only related with the transmitted waveform and bistatic geometry and could be regarded as the potential resolution of a bistatic radar system,the practical resolution involves the effect of waveform,signal-to-noise ratio(SNR)as well as the measurement model.Thus,it is more practical and will have further significant application in target detection and tracking.The constraint optimization procedure of joint adaptive waveform design and baseline range design for maximizing the practical resolution of bistatic radar system under dynamic target scenario was devised.Simulation results show that the range and velocity resolution are enhanced according to the adaptive waveform and bistatic radar configuration.

Recovery of saturated signal waveform acquired from high-energy particles with artificial neural networks

Artificial neural networks(ANNs)are a core component of artificial intelligence and are frequently used in machine learning.In this report,we investigate the use of ANNs to recover the saturated signals acquired in highenergy particle and nuclear physics experiments.The inherent properties of the detector and hardware imply that particles with relatively high energies probably often generate saturated signals.Usually,these saturated signals are discarded during data processing,and therefore,some useful information is lost.Thus,it is worth restoring the saturated signals to their normal form.The mapping from a saturated signal waveform to a normal signal waveform constitutes a regression problem.Given that the scintillator and collection usually do not form a linear system,typical regression methods such as multi-parameter fitting are not immediately applicable.One important advantage of ANNs is their capability to process nonlinear regression problems.To recover the saturated signal,three typical ANNs were tested including backpropagation(BP),simple recurrent(Elman),and generalized radial basis function(GRBF)neural networks(NNs).They represent a basic network structure,a network structure with feedback,and a network structure with a kernel function,respectively.The saturated waveforms were produced mainly by the environmental gamma in a liquid scintillation detector for the China Dark Matter Detection Experiment(CDEX).The training and test data sets consisted of 6000 and 3000 recordings of background radiation,respectively,in which saturation was simulated by truncating each waveform at 40%of the maximum signal.The results show that the GBRF-NN performed best as measured using a Chi-squared test to compare the original and reconstructed signals in the region in which saturation was simulated.A comparison of the original and reconstructed signals in this region shows that the GBRF neural network produced the best performance.This ANN demonstrates a powerful efficacy in terms of solving the saturation recovery problem.The proposed method outlines new ideas and possibilities for the recovery of saturated signals in high-energy particle and nuclear physics experiments.This study also illustrates an innovative application of machine learning in the analysis of experimental data in particle physics.

Inversion of receiver function by wavelet transformation

A new method for receiver function inversion by wavelet transformation is presented in this paper. Receiver func-tion is expanded to different scales with different resolution by wavelet transformation. After an initial model be-ing taken, a generalized least-squares inversion procedure is gradually carried out for receiver function from low to high scale, with the inversion result for low order receiver function as the initial model for high order. A neighborhood containing the global minimum is firstly searched from low scale receiver function, and will gradu-ally focus at the global minimum by introducing high scale information of receiver function. With the gradual ad-dition of high wave-number to smooth background velocity structure, wavelet transformation can keep the inver-sion result converge to the global minimum, reduce to certain extent the dependence of inversion result on the initial model, overcome the nonuniqueness of generalized least-squares inversion, and obtain reliable crustal and upper mantle velocity with high resolution.

Study of frequency domain full waveform inversion based on Huber norm and L-BFGS algorithm

Full waveform inversion( FWI) is a high resolution inversion method,which can reveal detailed information of the structure and lithology under complex geological background. It is limited by many kinds of noises when the method applied to the real seismic data. Based on Huber function criterion,the objective function combinates the anti-noise of L1 norm and the stability of L2 norm in theory,the authors derive the gradient formula of the Huber function by using L-BFGS algorithm for FWI. The new method is proved by synthetic seismic data with the Gaussian noise and the impulse noise. Numerical test results show that L-BFGS algorithm is applied to the frequency domain FWI with the convergence speed and high calculation accuracy,and can effectively reduce computer memory usage; and the Huber function is more robust and stable than L2 norm even with the noises.

基于优化波形叠加的井中微地震定位方法

基于波形叠加的微地震事件偏移定位技术因其具有不依赖于初至拾取精度的优势,逐渐被应用于非常规油气储层压裂监测资料处理。然而在相对低信噪比情况下,该类技术的常规成像函数分辨率会在一定程度上受到影响。为此,基于前人的研究成果,对波形相似性加权振幅叠加的成像函数构造方法进行了改进,提出一种优化波形叠加的井中微地震定位方法。首先将纵、横波波形相似性基函数进行相乘,再将其振幅叠加基函数进行相乘,然后将这两个乘积再相乘,最后在整个时窗内对其求和。该方法可提高波形叠加成像函数的分辨率。理论测试结果表明,与常规方法相比,改进方法具有更强的抗噪性和更高的定位精度。最后将常规方法与改进方法应用于井中监测的实际微地震数据,验证了方法的有效性。

Full waveform inversion based on initial model built from envelope inversion

Full waveform inversion is a fitting process based on full seismic wave field simulation data using the full waveform information in seismic records and theoretically it is the ultimate goal of seismic inversion. However,there are many problems to be solved in practical application. Firstly,it is the strong nonlinear problem between the seismic wave field and inversion parameters; secondly,the lack of low-frequency information in seismic records. In this study,the envelope is used as objective function inversion to provide the inversion result for the multi-scale full waveform inversion as the initial model,solving the lack of low-frequency information in seismic records. Taking the envelope of seismic records as the objective function in combination of multi-scale full waveform inversion became a new inversion strategy,which naturally achieved the compensation of shortage of low-frequency information and inversion from low frequency to high frequency,reducing the non-linearity in the inversion process. The comparison of the result of full waveform inversion of the initial model built through envelope inversion with the result of the conventional multi-scale full waveform inversion indicates the effectiveness of envelope inversion for the recovery of low-frequency information in seismic records.

ORTHOGONAL DISCRETE FREQUENCY-CODING WAVEFORM DESIGN FOR MIMO RADAR

Design of orthogonal code sets with ideal correlation properties is crucial for orthogonalMultiple Input Multiple Output(MIMO)radar.A modified Genetic Algorithm(GA)is proposed tonumerically design orthogonal Discrete Frequency-Coding Waveforms(DFCWs)with good correlationproperties for MIMO radar.Some of the designed results are presented,and their correlation propertiesare better than those presented in literatures.The effect of Doppler frequency shift on the performanceof these signals is simply investigated.Simulation results and comparisons show that the proposedalgorithm is more effective for the design of DFCWs with superior aperiodic correlation properties.

Extended ambiguity function for bistatic MIMO radar

This paper derives the extended ambiguity function for a bistatic multiple-input multiple-output （MIMO） radar system, which includes the whole radar system parameters： geometric sensor configuration, waveforms, range, range rate, target scattering and noise characteristics. Recent research indicates the potential pa- rameter estimate performance of bistatic MIMO radars. And this ambiguity function can be used to analyze the parameter estimate performance for the relationship with the Cramer-Rao bounds of the estimated parameters. Finally, some examples are given to demonstrate the good parameter estimate performance of the bistatic MIMO radar, using the quasi-orthogonal waveforms based on Lorenz chaotic systems.