Intelligent recognition and information extraction of radar complex jamming based on time-frequency features

In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more randomly.It is challenging for the radar to efficiently identify jamming and obtain precise parameter information,particularly in low signal-to-noise ratio(SNR)situations.In this paper,an approach to intelligent recognition and complex jamming parameter estimate based on joint time-frequency distribution features is proposed to address this challenging issue.Firstly,a joint algorithm based on YOLOv5 convolutional neural networks(CNNs)is proposed,which is used to achieve the jamming signal classification and preliminary parameter estimation.Furthermore,an accurate jamming key parameters estimation algorithm is constructed by comprehensively utilizing chi-square statistical test,feature region search,position regression,spectrum interpolation,etc.,which realizes the accurate estimation of jamming carrier frequency,relative delay,Doppler frequency shift,and other parameters.Finally,the approach has improved performance for complex jamming recognition and parameter estimation under low SNR,and the recognition rate can reach 98%under−15 dB SNR,according to simulation and real data verification results.

TVAR Time-frequency Analysis for Non-stationary Vibration Signals of Spacecraft

Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.

A Method in Mixed Frequency-time domain for Fatigue Life Estimation of Steel Girders of Cable-stayed Bridges Due to Buffeting

发展了斜拉桥钢主梁抖振疲劳寿命的混合时－频域方法．在本方法中，首先建立了桥面处的风速风向概率密度函数，导出的应力谱因其包括背景分量而不再是窄带谱．据应力谱模拟出了疲劳应力的时间历程，并用雨流计数法统计了其幅值特性．基于修正的Ｍｉｎｅｒ定理导出了考虑风速风向作用的桥梁主梁抖振疲劳寿命的估算公式，并用此分析了杨浦大桥钢主梁的抖振疲劳寿命．结果表明，风向对抖振疲劳寿命有很大影响；杨浦大桥主梁的疲劳寿命远大于设计寿命．

High-Precision Doppler Frequency Estimation Based Positioning Using OTFS Modulations by Red and Blue Frequency Shift Discriminator

Orthogonal Time Frequency and Space(OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Doppler frequency for positioning is a promising research direction on communication and navigation integration. To tackle the high Doppler frequency and low signal-to-noise ratio(SNR) in satellite communication, this paper proposes a Red and Blue Frequency Shift Discriminator(RBFSD) based on the pseudo-noise(PN) sequence.The paper derives that the cross-correlation function on the Doppler domain exhibits the characteristic of a Sinc function. Therefore, it applies modulation onto the Delay-Doppler domain using PN sequence and adjusts Doppler frequency estimation by red-shifting or blue-shifting. Simulation results show that the performance of Doppler frequency estimation is close to the Cramér-Rao Lower Bound when the SNR is greater than -15dB. The proposed algorithm is about 1/D times less complex than the existing PN pilot sequence algorithm, where D is the resolution of the fractional Doppler.

A NEW METHOD FOR FINDING THE NATURAL FREQUENCY SET OF A LINEAR TIME-INVARIANT NETWORK

This paper presents a new method for finding the natural frequency set of a linear time invariant network. In the paper deriving and proving of a common equation are described. It is for the first time that in the common equation the natural frequencies of an n th order network are correlated with the n port parameters. The equation is simple and dual in form and clear in its physical meaning. The procedure of finding the solution is simplified and standardized, and it will not cause the loss of roots. The common equation would find wide use and be systematized.

Primary frequency control considering communication delay for grid-connected offshore wind power systems

Offshore wind farms are becoming increasingly distant from onshore centralized control centers,and the communication delays between them inevitably introduce time delays in the measurement signal of the primary frequency control.This causes a deterioration in the performance of the primary frequency control and,in some cases,may even result in frequency instability within the power system.Therefore,a frequency response model that incorporates communication delays was established for power systems that integrate offshore wind power.The Padéapproximation was used to model the time delays,and a linearized frequency response model of the power system was derived to investigate the frequency stability under different time delays.The influences of the wind power proportion and frequency control parameters on the system frequency stability were explored.In addition,a Smith delay compensation control strategy was devised to mitigate the effects of communication delays on the system frequency dynamics.Finally,a power system incorporating offshore wind power was constructed using the MATLAB/Simulink platform.The simulation results demonstrate the effectiveness and robustness of the proposed delay compensation control strategy.

The time and frequency system of the Tianma 65 m radio telescope

A time and frequency system is a critical component of Very Long Baseline Interferometry(VLBI)stations,providing stable and reliable standards that directly impact data processing quality.At the Tianma 65 m radio telescope(TMRT),this system has been meticulously designed to ensure long-term reliability and high performance.It incorporates high-performance hydrogen atomic clocks,high-precision time standards,automatic signal switching,and robust system software.This comprehensive approach has enabled the system to achieve long-term reliable operation,successfully supporting both major national engineering tasks and daily scientific observations.The effectiveness of the system is evidenced by its consistent delivery of the precision and stability required for radio astronomy.This article provides an in-depth exploration of the design and operation of the time and frequency system at the Tianma 65 m telescope,examining various aspects of its architecture,implementation,and performance.By sharing these insights,we aim to contribute knowledge that could benefit similar systems at other VLBI stations,greatly advancing radio astronomy infrastructure.

Fuzzy-Model-Based Finite Frequency Fault Detection Filtering Design for Two-Dimensional Nonlinear Systems

This article studies the fault detection filtering design problem for Roesser type two-dimensional(2-D)nonlinear systems described by uncertain 2-D Takagi-Sugeno(T-S)fuzzy models.Firstly,fuzzy Lyapunov functions are constructed and the 2-D Fourier transform is exploited,based on which a finite frequency fault detection filtering design method is proposed such that a residual signal is generated with robustness to external disturbances and sensitivity to faults.It has been shown that the utilization of available frequency spectrum information of faults and disturbances makes the proposed filtering design method more general and less conservative compared with a conventional nonfrequency based filtering design approach.Then,with the proposed evaluation function and its threshold,a novel mixed finite frequency H_(∞)/H_(-)fault detection algorithm is developed,based on which the fault can be immediately detected once the evaluation function exceeds the threshold.Finally,it is verified with simulation studies that the proposed method is effective and less conservative than conventional non-frequency and/or common Lyapunov function based filtering design methods.

Robust H_∞ Load Frequency Control of Multi-area Power System With Time Delay:A Sliding Mode Control Approach

This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of renewable energies,a new sliding surface function is constructed to guarantee the fast response and robust performance, then the sliding mode control law is designed to guarantee the reach ability of the sliding surface in a finite-time interval. The sufficient robust frequency stabilization result for multi-area power system with time delay is presented in terms of linear matrix inequalities(LMIs). Finally,a two-area power system is provided to illustrate the usefulness and effectiveness of the obtained results.

Applications of Fractional Lower Order Time-frequency Representation to Machine Bearing Fault Diagnosis

The machinery fault signal is a typical non-Gaussian and non-stationary process. The fault signal can be described by SaS distribution model because of the presence of impulses.Time-frequency distribution is a useful tool to extract helpful information of the machinery fault signal. Various fractional lower order(FLO) time-frequency distribution methods have been proposed based on fractional lower order statistics, which include fractional lower order short time Fourier transform(FLO-STFT), fractional lower order Wigner-Ville distributions(FLO-WVDs), fractional lower order Cohen class time-frequency distributions(FLO-CDs), fractional lower order adaptive kernel time-frequency distributions(FLO-AKDs) and adaptive fractional lower order time-frequency auto-regressive moving average(FLO-TFARMA) model time-frequency representation method.The methods and the exiting methods based on second order statistics in SaS distribution environments are compared, simulation results show that the new methods have better performances than the existing methods. The advantages and disadvantages of the improved time-frequency methods have been summarized.Last, the new methods are applied to analyze the outer race fault signals, the results illustrate their good performances.

Time-and Frequency-Domain Analysis of Ice-Induced Displacement Responses Offshore Fixed Platforms

On the basis of ice- induced forced vibration model, ice- induced displacement responses of offshore fixed platforms are investigated in both time domain and frequency domain. The relationships of ice-induced displacement responses with ice breaking modes, ice acting directions and platform structures are analyzed and determined. The results lead to an important conclusion obtained for the first time that ice breaking frequency and the natural frequency of the first mode of the platform are the two main factors that dominate the degree of vibration. The present work provides a firm basis for both design and operation of fixed platforms against ice loading.

Experimental validation of a signal-based approach for structural earthquake damage detection using fractal dimension of time frequency feature

This article extends a signal-based approach formerly proposed by the authors, which utilizes the fractal dimension of time frequency feature （FDTFF） of displacements, for earthquake damage detection of moment resist frame （MRF）, and validates the approach with shaking table tests. The time frequency feature （TFF） of the relative displacement at measured story is defined as the real part of the coefficients of the analytical wavelet transform. The fractal dimension （FD） is to quantify the TFF within the fundamental frequency band using box counting method. It is verified that the FDTFFs at all stories of the linear MRF are identical with the help of static condensation method and modal superposition principle, while the FDTFFs at the stories with localized nonlinearities due to damage will be different from those at the stories without nonlinearities using the reverse-path methodology. By comparing the FDTFFs of displacements at measured stories in a structure, the damage-induced nonlinearity of the structure under strong ground motion can be detected and localized. Finally shaking table experiments on a 1：8 scale sixteen-story three-bay steel MRF with added frictional dampers, which generate local nonlinearities, are conducted to validate the approach.

Adaptive Fourier Decomposition Based Time-Frequency Analysis

The attempt to represent a signal simultaneously in time and frequency domains is full of challenges. The recently proposed adaptive Fourier decomposition （AFD） offers a practical approach to solve this problem. This paper presents the principles of the AFD based time-frequency analysis in three aspects： instantaneous frequency analysis, frequency spectrum analysis, and the spectrogram analysis. An experiment is conducted and compared with the Fourier transform in convergence rate and short-time Fourier transform in time-frequency distribution. The proposed approach performs better than both the Fourier transform and short-time Fourier transform.

Numerical Prediction Methods for Clock Deviation Based on Two-Way Satellite Time and Frequency Transfer Data

Three functional models, polynomial, spectral analysis, and modified AR model, are studied and compared in fitting and predicting clock deviation based on the data sequence derived from two-way satellite time and frequency transfer. A robust equivalent weight is applied, which controls the significant influence of outlying observations. Some conclusions show that the prediction precision of robust estimation is better than that of LS. The prediction precision calculated from smoothed observations is higher than that calculated from sampling observations. As a count of the obvious period variations in the clock deviation sequence, the predicted values of polynomial model are implausible. The prediction precision of spectral analysis model is very low, but the principal periods can be determined. The prediction RMS of 6-hour extrapolation interval is Ins or so, when modified AR model is used.

Fiber-based joint time and frequency dissemination via star-shaped commercial telecommunication network

A fiber-based, star-shaped joint time and frequency dissemination scheme is demonstrated. By working in cooperation with the existing commercial telecommunication network. Our scheme enables the frequency, time, and digital data networks to be integrated together and could represent an ideal option of interconnection among scientific institutions.The compensation functions of the time and frequency transfer scheme are set at the client nodes. The complexity of the central node is thus reduced, and future expansion by the addition of further branches will be accomplished more easily.During a performance test in which the ambient temperature fluctuation is 30℃/day, timing signal dissemination stability is achieved to be approximately ±50 ps along 25-km-long fiber spools. After calibration, a timing signal synchronization accuracy of 100 ps is also realized. The proposed scheme offers an option of the construction of large-scale fiber-based frequency and time transfer networks.

Joint transfer of time and frequency signals and multi-point synchronization via fiber network

A system of jointly transferring time signals with a rate of 1 pulse per second （PPS） and frequency signals of 10 MHz via a dense wavelength division multiplex-based （DWDM） fiber is demonstrated in this paper. The noises of the fiber links are suppressed and compensated for by a controlled fiber delay line. A method of calibrating and characterizing time is described. The 1PPS is synchronized by feed-forward calibrating the fiber delays precisely. The system is experimen- tally examined via a 110 km spooled fiber in laboratory. The frequency stabilities of the user end with compensation are 1.8x 10-14 at 1 s and 2.0x 10-17 at 104 s average time. The calculated uncertainty of time synchronization is 13.1 ps, whereas the direct measurement of the uncertainty is 12 ps. Next, the frequency and 1PPS are transferred via a metropoli- tan area optical fiber network from one central site to two remote sites with distances of 14 km and 110 km. The frequency stabilities of 14 km link reach 3.0x 10-14 averaged in 1 s and 1.4x 10-17 in 104 s respectively; and the stabilities of 110 km link are 8.3 x 10-14 and 1.7 x 10-17, respectively. The accuracies of synchronization are estimated to be 12.3 ps for the 14 km link and 13.1 ps for the 110 km link, respectively.

Higher Order Moment Spectra Time-Frequency Analysis of the Geophysical Signal

On the basis of an introduction of the Wigner Higher-Order spectra (WHOS) and a general class of time-frequency higher-order moment spectra, the geophysical signal was analyzed using the higher order time-frequency distributions (TFD). Simulation results obtained in this paper show that the higher-order TFD (Wigner Bispectrum, Wigner Trispectrum and Choi-Williams Trispectrum) have much better Time-Frequency Concentration than the second-order TFD, and the reduced interference higher-order TFD such as CWT can effectively reduce the cross-term in multicomponent signals and simultaneously obtain high time-frequency concentration.

Static-Output-Feedback Based Robust Fuzzy Wheelbase Preview Control for Uncertain Active Suspensions With Time Delay and Finite Frequency Constraint

This paper proposes a static-output-feedback based robust fuzzy wheelbase preview control algorithm for uncertain active suspensions with time delay and finite frequency constraint.Firstly,a Takagi-Sugeno(T-S)fuzzy augmented model is established to formulate the half-car active suspension system with consideration of time delay,sprung mass variation and wheelbase preview information.Secondly,in view of the resonation between human’s organs and vertical vibrations in the frequency range of 4–8 Hz,a finite frequency control criterion in terms of H∞norm is developed to improve ride comfort.Meanwhile,other mechanical constraints are also considered and satisfied via generalized H2 norm.Thirdly,in order to maintain the feasibility of the controller despite of some state variables are not online-measured,a two stage approach is adopted to derive a static output feedback controller.Finally,numerical simulation results illustrate the excellent performance of the proposed controller.

Modeling of cascaded high isolation bidirectional amplification in long-distance fiber-optic time and frequency synchronization system

We propose a physical model of estimating noise and asymmetry brought by high isolation Bi-directional erbiumdoped fiber amplifiers(Bi-EDFAs),no spontaneous lasing even with high gain,in longdistance fiber-optic time and frequency(T/F)synchronization system.It is found that the Rayleigh scattering noise can be suppressed due to the high isolation design,but the amplified spontaneous emission(ASE)noise generated by the high isolation Bi-EDFA and the bidirectional asymmetry of the transmission link caused by the high isolation Bi-EDFA will deteriorate the stability of the system.The calculated results show that under the influence of ASE noise,the frequency instability of a 1200 km system composed of 15 high isolation Bi-EDFAs is 1.773×10^(-13)/1 s.And the instability caused by asymmetry is 2.6064×10^(-16)/30000–35000 s if the total asymmetric length of the bidirectional link length is 30 m.The intensity noises originating from the laser and detector,the transfer delay fluctuations caused by the variation in ambient temperature and the jitter in laser output wavelength are also studied.The experiment composed of three high isolation Bi-EDFAs is done to confirm the theoretical analysis.In summary,the paper shows that the short-term instability of the T/F synchronization system composed of high isolation Bi-EDFAs is limited by the accumulation of ASE noise of amplifiers and the laser frequency drift,while the long-term instability is limited by the periodic variation in ambient temperature and the asymmetry of the amplifiers.The research results are useful for pointing out the direction to improve the stability of the fiber-optic T/F synchronization system.

Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.