A nonparametric spectrum estimation method for dispersion and attenuation analysis of borehole acoustic measurements

Dispersion and attenuation analysis can be used to determine formation anisotropy induced by fractures,or stresses.In this paper,we propose a nonparametric spectrum estimation method to get phase dispersion characteristics and attenuation coefficient.By designing an appropriate vector filter,phase velocity,attenuation coefficient and amplitude can be inverted from the waveform recorded by the receiver array.Performance analysis of this algorithm is compared with Extended Prony Method(EPM)and Forward and Backward Matrix Pencil(FBMP)method.Based on the analysis results,the proposed method is capable of achieving high resolution and precision as the parametric spectrum estimation methods.At the meantime,it also keeps high stability as the other nonparametric spectrum estimation methods.At last,applications to synthetic waveforms modeled using finite difference method and real data show its efficiency.The real data processing results show that the P-wave attenuation log is more sensitive to oil formation compared to S-wave;and the S-wave attenuation log is more sensitive to shale formation compared to P-wave.

Application of X-band Polarimetric Phased-array Radars in Quantitative Precipitation Estimation

The performance of different quantitative precipitation estimation(QPE) relationships is examined using the polarimetric variables from the X-band polarimetric phased-array radars in Guangzhou,China.Three QPE approaches,namely,R(ZH),R(ZH,ZDR) and R(KDP),are developed for horizontal reflectivity,differential reflectivity and specific phase shift rate,respectively.The estimation parameters are determined by fitting the relationships to the observed radar variables using the T-matrix method.The QPE relationships were examined using the data of four heavy precipitation events in southern China.The examination shows that the R(ZH) approach performs better for the precipitation rate less than 5 mm h-1, and R(KDP) is better for the rate higher than 5 mm h-1, while R(ZH,ZDR) has the worst performance.An adaptive approach is developed by taking the advantages of both R(ZH) and R(KDP) approaches to improve the QPE accuracy.

Refractivity estimations from an angle-of-arrival spectrum

This paper addresses the probability of atmospheric refractivity estimation by using field measurements at an array of radio receivers in terms of angle-of-arrival spectrum. Angle-of-arrival spectrum information is simulated by the ray optics model and refractivity is expressed in the presence of an ideal tri-linear profile. The estimation of the refractivity is organized as an optimization problem and a genetic Mgorithm is used to search for the optimal solution from various trial refractivity profiles. Theoretical analysis demonstrates the feasibility of this method to retrieve the refractivity parameters. Simulation results indicate that this approach has a fair anti-noise ability and its accuracy performance is mainly dependent on the antenna aperture size and its positions.

SAR STEREO IMAGING ALGORITHM BASED ON CAPON SPECTRUM ESTIMATION

This letter presents a novel approach for the Synthetic Aperture Radar (SAR) stereo imaging based on the Capon spectrum estimation technique. In order to deal with nonuniform sampling space and lead to super resolution in the elevation direction, Capon approach is used to focus the SAR data on a certain height. Results obtained on simulated data demonstrate the feasibility of the Capon based algorithm. Compared with the classical Fast Fourier Transform (FFT), the Capon based algo-rithm shows better resolution quality.

SPATIAL SPECTRUM ESTIMATION OF COHERENT SOURCES IMPINGING ON NONUNIFORM ARRAYS

The problem of bearing estimation of coherent signal impingiog on an array ofarbitrary geometry is studied.Both approaches are developed,the first one synthesizes theobserved array data into the outputs of a linear uniform array and then processes them viaconventional techniques such as spatial smoothing etc.The second approach is based on theinvariant subspace rotation operation which is equivalent to the translational displacement ofthe artay,linearly independent signal vectors are obtained thereby to span perfectly the signalsubspace.As compared with the conventional processing techniques,the approach based oninvariant subspace rotation does not lead to an effective decrease in aperture size and thereforea decrease in resolution capability.The computer simulations are conducted to demonstrate theeffectiveness of the presented approaches.

Estimation of dynamic stress spectrum distribution in structural fatigue test

The determination of structural dynamic stress spectrum distribution is of great signifi- cance in the structural fatigue strength evaluation as well as reliability design. In previous empirical data processing methods, the data grouping and distribution fitting were excessively coarse and contained distinctive defects. This paper proposed an effective approach to statistically group actual measured dynamic stress data and validly extrapolate the combined distribution to fit the dynamic stress spectrum distribution. This approach has been verified its effectiveness through chi-square test, stress spectrum extrapolation and damage calculation in dynamic stress study.

Direction of Arrival Estimation under Spread Spectrum Reference Signal Assisted Radio

In the present work, a direction of arrival estimator, under spread spectrum reference of signal-assisted radio operating in a Rayleigh fading channel, is proposed. The analysis, which is applied to general receiver antenna array configurations, demonstrates the high performance of the estimator which is due to the double dispreading (code word and reference signal). The probability distribution function of the estimator is extracted and the system’s robustness in regard to large number of interferers is demonstrated.

Maximum likelihood spectrum estimation method and its application in seismo－magnet－icrelation

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Spectrum Requirements Estimation for the Future IMT Systems: Current Work and Way Forward

In order to satisfy the spectrum requirements of the future international mobile telecommunication (IMT) systems, to realize scientific allocation and usage of spectrum resources and to avoid spectrum waste brought by allocation in advanced, there is a need to make a reasonable estimation for the spectrum demands of future IMT systems. The estimation results can also provide guidelines for the subsequent spectrum planning and assignment work. This paper gives a description of study progress of related spectrum estimation for future IMT systems. From the analysis of current work and practical situation, the key factors in the estimation methodology are summarized to provide a reference for the following work.

S-transformation based integrated approach for spectrum estimation, storage, and sensing in cognitive radio

Cognitive Radio (CR) uses the principle of dynamic spectrum allocation to improve the utilization of spectrum bands. The estimation of missing data is essential for maintaining an uninterrupted quality of service in the CR. However, the existing methods are not suitable for interpolating missing data in high frequency signals. The storage of spectrum occupancy information is crucial for learning the spectrum usage and prediction. The existing techniques for wideband spectrum sensing suffer from poor edge detection capabilities. This paper proposes an STransformation (ST) based approach to solve these problems. For missing samples, the proposed method improves the accuracy of estimation. The ST can also be used to store the spectrum occupancy information. The simulation results show that the proposed scheme outperforms others by improving the accuracy of edge detection. Further, the simple implementation of the ST in the frequency domain is an advantage for the real time application.

IRS-Enabled Spectrum Sharing:Interference Modeling,Channel Estimation and Robust Passive Beamforming

Intelligent reflecting surface(IRS),with its unique capability of smartly reconfiguring wireless channels,provides a new solution to improving spectrum efficiency,reducing energy consumption and saving deployment/hardware cost for future wireless networks.In this paper,IRS-enabled spectrum sharing is investigated,from the perspectives of interference modeling,efficient channel estimation and robust passive beamforming design.Specifically,we first characterize the interference in a spectrum sharing system consisting of a single primary user(PU)pair and a single secondary user(SU)pair,and extend it to the large-scale network by leveraging the Poisson point process(PPP).Then,we propose an efficient channel estimation framework based on decoupling the cascaded IRS channels.Moreover,the tradeoff between spectrum efficiency and energy efficiency is derived from the view of channel estimation accuracy.Finally,we discuss the robust passive beamforming design in presence of imperfect channel estimation and nonideal/discrete phase shifts.It is hoped that this paper provides useful guidance for unlocking the full potential of IRS for achieving efficient spectrum sharing for future wireless networks.

2-D SPATIAL-SPECTRUM ESTIMATION FORWIDE-BAND SOURCES BASED ON INTERPOLATED CIRCULAR ARRAYS

In array signal processing, 2-D spatial-spectrum estimation is required to determine DOA of multiple signals. The circular array of sensors is found to possess several nice properties for DOA estimation of wide-band sources. C. U. Padmini, et al.(1994) had suggested that the frequency-direction ambiguity in azimuth estimation of wide-baud signals received by a uniform linear array (ULA) can be avoided by using a circular array, even without the use of any delay elements. In 2-D spatial-spectrum estimation for wide-band signals, the authors find that it is impossible to avoid the ambiguity in source frequency-elevation angle pairs using a circular array. In this paper, interpolated circular arrays are used to perform 2-D spatial-spectrum estimation for wide-band sources. In the estimation, a large aperture circular array (Υ】λmin/2) is found to possess superior resolution capability and robustness.

NEW AUTOREGRESSIVE MOVING AVERAGE SPECTRUM ESTIMATION AND CEPSTRUM ALGORITHM

Based on the deduction of the C parameter estimation, a new method to estimate C Parameters from the AR parameters of the ARMA model and auto-related function is proposed , The method reduces the computation complexity of the conventional interative algorithm in MA parameter estimation, thus make the algorithm of ARMA model spectral estimation simpler. On account of this method, a new algo- rithm of cepstrum analysis is put forward . Computer simulation indicates that the proposed cepstrum al- gorithm has the merits of few sidelobes and high resolution . And the algorithm is very useful to the ding- nosis of machinery failure .

Approach to blind estimation of the PN sequence in DS-SS signals with residual carrier

This paper presents an approach of singular value de- composition plus digital phase lock loop to solve the difficult problem of blind pseudo-noise （PN） sequence estimation in low signal to noise ratios （SNR） direct sequence spread spectrum （DS-SS） signals with residual carrier. This approach needs some given parameters, such as the period and code rate of PN sequence. The received signal is firstly sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. An autocorrelation matrix is then computed and accumulated by those signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of the autocorrelation matrix. Further more, a digital phase lock loop is used to process the estimated PN sequence, it estimates and tracks the residual carrier and removes the residual carrier in the end. Theory analysis and computer simulation results show that this approach can effectively realize the PN sequence blind estimation from the input DS-SS signals with residual carrier in lower SNR.

Fast method for spreading sequence estimation of DSSS signal based on maximum likelihood function

To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).

Ultrasonic attenuation estimation based on time-frequency analysis

The quality factor(or Q value)is an important parameter for characterizing the inelastic properties of rock.Achieving a Q value estimation with high accuracy and stability is still challenging.In this study,a new method for estimating ultrasonic attenuation using a spectral ratio based on an S transform(SR-ST)is presented to improve the stability and accuracy of Q estimation.The variable window of ST is used to solve the time window problem.We add two window factors to the Gaussian window function in the ST.The window factors can adjust the scale of the Gaussian window function to the ultrasonic signal,which reduces the calculation error attributed to the conventional Gaussian window function.Meanwhile,the frequency bandwidth selection rules for the linear regression of the amplitude ratio are given to further improve stability and accuracy.First,the feasibility and influencing factors of the SR-ST method are studied through numerical testing and standard sample experiments.Second,artificial samples with different Q values are used to study the adaptability and stability of the SR-ST method.Finally,a further comparison between the new method and the conventional spectral ratio method(SR)is conducted using rock field samples,again addressing stability and accuracy.The experimental results show that this method will yield an error of approximately 36%using the conventional Gaussian window function.This problem can be solved by adding the time window factors to the Gaussian window function.The frequency bandwidth selection rules and mean slope value of the amplitude ratio used in the SR-ST method can ensure that the maximum error of different Q values estimation(Q>15)is less than 10%.

Linear Support Vector Machine Based Inter-harmonic Modeling and Parameter Estimation

There are often system. The high measure many inter-harmonics in power t accuracy of inter-harmonics order, amplitude and initial phase is needed. A new approach is presented for inter-harmonic modeling and parameter estimation based on linear support vector machine （SVM）. Firstly, parameter estimation of linear model is realized based on standard linear SVM. Then, interharmonic model is transformed to a linear model according to trigonometric functions. The approach obtains order of inter-harmonic model with windowed Blackman-Tukey （BT） spectrum analysis, and gets number and frequency of harmonics. Finally, the linear SVM is applied to estimate the inter-harmonic parameters, amplitude and initial phase. The simulation results show that the proposed approach has high precision and good antinoise. The accuracy of three parameters are all higher than 98%.

A NOVEL UNIVERSAL PREPROCESSING APPROACH FOR HIGH-RESOLUTION DIRECTION-OF-ARRIVAL ESTIMATION

A novel universal preprocessing method is proposed to estimate angles of arrival,which is applicable to one-or two-dimensional high resolution processing based on arbitrarycenter-symmetric arrays (such as uniform linear arrays, equal-spaced rectangular planar arraysand symmetric circular arrays). By mapping the complex signal space into the real one, the newmethod can effectively reduce the computation needed by the signal subspace direction findingtechniques without any performance degradation. In addition, the new preprocessing scheme itselfcan decorrelate the coherent signals received on the array. For regular array geometry such asuniform linear arrays and equal-spaced rectangular planar arrays, the popular spatial smoothingpreprocessing technique can be combined with the novel approach to improve the decorrelatingability. Simulation results confirm the above conclusions.

INTERFERENCE ESTIMATION AND ITS APPLICATIONS IN COGNITIVE RADIO NETWORKS

Cognitive Radio(CR) has been proposed as a system-level means to improve the spectrum utilization efficiency.The most significant premise for CR networks is to avoid harmful interference to the licensed users.Therefore,it is very important to estimate the potential inter-ference introduced by the deployment of CR networks so that CR networks can be coexistence with Licensed User(LU) networks by designing proper system parameters.In this paper,two statistical models of potential interference due to CR networks are developed based on transmitter and receiver oriented spectrum sensing schemes,respectively.The approximate probability dis-tributions of aggregate interference introduced by CR networks are then derived with respect to the obtained models.With the help of these probability distributions,a method is further pre-sented to get the critical system parameter,i.e.,sensing distance and user density of the CR networks,so that the introduced interference can be controlled to predefined level.Numerical results validate the proposed interference estimation method and confirm the effectiveness of in-terference distribution based system parameter design.

基于重构健康指标的锂电池容量估计

针对锂电池搁置引起的退化特征局部再生分量和噪声波动分量所呈现出的非线性和非平稳性,利用奇异谱分析方法对健康指标中蕴含的主要衰退特征和噪声信号进行识别和分离得到了重构健康指标。使用马里兰大学高级生命周期工程中心(CALCE)锂电池数据集中CS2-35,CS2-36和CS2-37电池数据对所提重构健康指标结合多项式回归进行容量估计的效果进行验证。结果表明,使用重构健康指标对锂离子电池容量估计的平均RMSE为0.030 2,平均MAE为0.022 3,且适应度系数超过0.98。对下一步进行锂离子电池剩余使用寿命在线预测具有重要意义。