In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the ...In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations.By optimizing the linear matching circuit with the optimal embedding impedance,the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit,substantially improving the speed of simulations.The design of on-chip linear matching circuits adopts a modular circuit design strategy,incorporating fixed load resistors to simplify the matching challenge.Utilizing this approach,a 340 GHz frequency doubler was developed and measured.The results demonstrate that,across a bandwidth of 330 GHz to 342 GHz,the efficiency of the doubler remains above 10%,with an input power ranging from 98 mW to 141mW and an output power exceeding 13 mW.Notably,at an input power of 141 mW,a peak output power of 21.8 mW was achieved at 334 GHz,corresponding to an efficiency of 15.8%.展开更多
Low-frequency signals have been proven valuable in the fields of target detection and geological exploration.Nevertheless,the practical implementation of these signals is hindered by large antenna diameters,limiting t...Low-frequency signals have been proven valuable in the fields of target detection and geological exploration.Nevertheless,the practical implementation of these signals is hindered by large antenna diameters,limiting their potential applications.Therefore,it is imperative to study the creation of lowfrequency signals using antennas with suitable dimensions.In contrast to conventional mechanical antenna techniques,our study generates low-frequency signals in the spatial domain utilizing the principle of the Doppler effect.We also defines the antenna array architecture,the timing sequency,and the radiating element signal waveform,and provides experimental prototypes including 8/64 antennas based on earlier research.In the conducted experiments,121 MHz,40 MHz,and 10 kHz composite signals are generated by 156 MHz radiating element signals.The composite signal spectrum matches the simulations,proving our low-frequency signal generating method works.This holds significant implications for research on generating low-frequency signals with small-sized antennas.展开更多
Dynamic disturbances certainly reduce shear strength of rock joints,yet the mechanism needs deeper explanation.We investigate the shear behavior of a rough basalt joint by conducting laboratory shear experiments.Const...Dynamic disturbances certainly reduce shear strength of rock joints,yet the mechanism needs deeper explanation.We investigate the shear behavior of a rough basalt joint by conducting laboratory shear experiments.Constant and superimposed oscillating normal loads are applied at the upper block.Meanwhile,the bottom block moves at a constant shear rate.We investigate the shear behavior by:1)altering the normal load oscillation frequency with a same shear rate,2)altering the shear rate with a same normal load oscillation frequency,and 3)altering the normal load oscillation frequency and shear rate simultaneously with a constant ratio.The results show that the oscillating normal load reduces the coefficient of friction(COF).The reduce degree of COF increases with higher shear rate,decreases when increasing normal load oscillation frequency,and keeps constant if the special ratio,v/f(shear rate divided by normal oscillation frequency),is constant.Moreover,we identify a time lag between peak normal load and peak shear load.And the lagging proportion increases with higher shear rate,and decreases with larger static COF.Our results imply that a lower creep rate with a higher normal load oscillation frequency easily destabilizes the creeping fault zones.展开更多
Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effectiv...Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.展开更多
This paper presents an algorithm that aims to reduce the peak-to-average power ratio（PAPR） of orthogonal frequency division multiplexing（OFDM） communication systems while maintaining frequency tracking.The algorit...This paper presents an algorithm that aims to reduce the peak-to-average power ratio（PAPR） of orthogonal frequency division multiplexing（OFDM） communication systems while maintaining frequency tracking.The algorithm achieves PAPR reduction by applying the complex conjugates of the data symbol obtained from the frequency domain to cancel the phase of the data symbol.A likelihood estimator is used to obtain the sub-carrier phase error due to the residual carrier frequency offset（RCFO） using the same complex conjugates as a pilot signal.Furthermore,a joint time and frequency domain multicarrier phase locked loop（MPLL） is developed to compensate additional frequency offset.Simulation results show that this algorithm is capable of reducing PAPR without impacting the frequency tracking performance.展开更多
For multiple-input multiple-output （MIMO） orthogonal frequency division multiplexing （OFDM） systems, a joint timing synchronization and frequency offset acquisition algorithm based on fractional Fourier transform ...For multiple-input multiple-output （MIMO） orthogonal frequency division multiplexing （OFDM） systems, a joint timing synchronization and frequency offset acquisition algorithm based on fractional Fourier transform （FRFT） is proposed. The linear frequency modulation signals superimposed on the data signals are used as the training signals. By performing FRFT on the received signals and searching the peak value of the FRFT results, the receiver can realize timing synchronization and frequency offset acquisition simultaneously. Compared with the existing methods, the proposed algorithm can provide better timing synchronization performance and larger frequency offset acquisition range even under multi-path channels with low signal to noise ratio. Theoretical analysis and simulation results prove this point.展开更多
In an orthogonal frequency division multiplexing(OFDM) system,a time and frequency domain least mean square algorithm(TF-LMS) was proposed to cancel the frequency offset(FO).TF-LMS algorithm is composed of two stages....In an orthogonal frequency division multiplexing(OFDM) system,a time and frequency domain least mean square algorithm(TF-LMS) was proposed to cancel the frequency offset(FO).TF-LMS algorithm is composed of two stages.Firstly,time domain least mean square(TD-LMS) scheme was selected to pre-cancel the frequency offset in the time domain,and then the interference induced by residual frequency offset was eliminated by the frequency domain mean square(FD-LMS) scheme in frequency domain.The results of bit error rate(BER) and quadrature phase shift keying(QPSK) constellation figures show that the performance of the proposed suppression algorithm is excellent.展开更多
The problem of channel estimation for multiple an- tenna orthogonal frequency division multiplexing （OFDM） systems subject to unknown carrier frequency offset （CFO） is addressed. Multiple signal classification （M...The problem of channel estimation for multiple an- tenna orthogonal frequency division multiplexing （OFDM） systems subject to unknown carrier frequency offset （CFO） is addressed. Multiple signal classification （MUSIC）-Iike algorithm, which generally has been used for direction estimation or frequency estimation, is used for channel estimation in multiple antenna OFDM systems. A reduced dimensional （RD）-MUSIC based algorithm for channel estimation is proposed in multiple antenna OFDM systems with unknown CFO. The Cramer-Rao bound （CRB） of channel estimation in multiple antenna OFDM systems with unknown CFO is derived. The proposed algorithm has a superior performance of channel estimation compared with the Capon method and the least squares method.展开更多
Carrier frequency offset （CFO） in MIMO-OFDM systems can be decoupled into two parts： fraction frequency offset （FFO） and integer frequency offset （IFO）. The problem of IFO estimation is addressed and a new IFO ...Carrier frequency offset （CFO） in MIMO-OFDM systems can be decoupled into two parts： fraction frequency offset （FFO） and integer frequency offset （IFO）. The problem of IFO estimation is addressed and a new IFO estimator based on the Bayesian philosophy is proposed. Also, it is shown that the Bayesian IFO estimator is optimal among all the IFO estimators. Furthermore, the Bayesian estimator can take advantage of oversampling so that better performance can be obtained. Finally, numerical results show the optimality of the Bayesian estimator and validate the theoretical analysis.展开更多
A tunable dual polarization absorption-transmission-absorption(A-T-A)frequency selective absorbers(FSR)to address the issue of high insertion loss in current tunable FSRs is proposed.The lumped resistors are loaded on...A tunable dual polarization absorption-transmission-absorption(A-T-A)frequency selective absorbers(FSR)to address the issue of high insertion loss in current tunable FSRs is proposed.The lumped resistors are loaded onto the lossy layer to absorb electromagnetic waves within the absorption band.The varactor diodes are loaded onto another lossless layer to control the transmission frequency band of the FSR.Its equivalent circuit model is provided.The proposed tunable FSR can change the passband within the range of 14.5~15.5 GHz by changing the bias voltage applied to the lossless transmission layer,while maintaining insertion loss above-1.67 dB.The series resonant structure of the lossy layer generates bilateral absorption bands between 10.2~13.5 GHz and 17.2~22 GHz,with broadband reflection suppression ranging from 10.3 GHz to 22 GHz(70.7%).The prototype is manufactured,and the measured results have verified the simulation results.展开更多
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 p...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.展开更多
基金Supported by the Beijing Municipal Science&Technology Commission(Z211100004421012),the Key Reaserch and Development Pro⁃gram of China(2022YFF0605902)。
文摘In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations.By optimizing the linear matching circuit with the optimal embedding impedance,the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit,substantially improving the speed of simulations.The design of on-chip linear matching circuits adopts a modular circuit design strategy,incorporating fixed load resistors to simplify the matching challenge.Utilizing this approach,a 340 GHz frequency doubler was developed and measured.The results demonstrate that,across a bandwidth of 330 GHz to 342 GHz,the efficiency of the doubler remains above 10%,with an input power ranging from 98 mW to 141mW and an output power exceeding 13 mW.Notably,at an input power of 141 mW,a peak output power of 21.8 mW was achieved at 334 GHz,corresponding to an efficiency of 15.8%.
基金Science and Technology Project of Aerospace Information Research Institute,Chinese Academy of Sciences(Y910340Z2F)Science and Technology Project of BBEF(E3E2010201)。
文摘Low-frequency signals have been proven valuable in the fields of target detection and geological exploration.Nevertheless,the practical implementation of these signals is hindered by large antenna diameters,limiting their potential applications.Therefore,it is imperative to study the creation of lowfrequency signals using antennas with suitable dimensions.In contrast to conventional mechanical antenna techniques,our study generates low-frequency signals in the spatial domain utilizing the principle of the Doppler effect.We also defines the antenna array architecture,the timing sequency,and the radiating element signal waveform,and provides experimental prototypes including 8/64 antennas based on earlier research.In the conducted experiments,121 MHz,40 MHz,and 10 kHz composite signals are generated by 156 MHz radiating element signals.The composite signal spectrum matches the simulations,proving our low-frequency signal generating method works.This holds significant implications for research on generating low-frequency signals with small-sized antennas.
基金Project(52474122)supported by the National Natural Science Foundation of ChinaProject(HSR202105)supported by the National Engineering Laboratory for High-speed Railway Construction,China+1 种基金Project(2025B1515020067)supported by the Natural Science Foundation of Guangdong Province of ChinaProject(2022A1515240009)supported by the Natural Science Foundation of Guangdong Province,China。
文摘Dynamic disturbances certainly reduce shear strength of rock joints,yet the mechanism needs deeper explanation.We investigate the shear behavior of a rough basalt joint by conducting laboratory shear experiments.Constant and superimposed oscillating normal loads are applied at the upper block.Meanwhile,the bottom block moves at a constant shear rate.We investigate the shear behavior by:1)altering the normal load oscillation frequency with a same shear rate,2)altering the shear rate with a same normal load oscillation frequency,and 3)altering the normal load oscillation frequency and shear rate simultaneously with a constant ratio.The results show that the oscillating normal load reduces the coefficient of friction(COF).The reduce degree of COF increases with higher shear rate,decreases when increasing normal load oscillation frequency,and keeps constant if the special ratio,v/f(shear rate divided by normal oscillation frequency),is constant.Moreover,we identify a time lag between peak normal load and peak shear load.And the lagging proportion increases with higher shear rate,and decreases with larger static COF.Our results imply that a lower creep rate with a higher normal load oscillation frequency easily destabilizes the creeping fault zones.
文摘Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.
基金supported by the National Natural Science Foundation of China(60872026)the Natural Science Foundation of Tianjin(09JCZDJC16900)
文摘This paper presents an algorithm that aims to reduce the peak-to-average power ratio（PAPR） of orthogonal frequency division multiplexing（OFDM） communication systems while maintaining frequency tracking.The algorithm achieves PAPR reduction by applying the complex conjugates of the data symbol obtained from the frequency domain to cancel the phase of the data symbol.A likelihood estimator is used to obtain the sub-carrier phase error due to the residual carrier frequency offset（RCFO） using the same complex conjugates as a pilot signal.Furthermore,a joint time and frequency domain multicarrier phase locked loop（MPLL） is developed to compensate additional frequency offset.Simulation results show that this algorithm is capable of reducing PAPR without impacting the frequency tracking performance.
基金supported by the National Natural Science Foundation of China(60672047).
文摘For multiple-input multiple-output （MIMO） orthogonal frequency division multiplexing （OFDM） systems, a joint timing synchronization and frequency offset acquisition algorithm based on fractional Fourier transform （FRFT） is proposed. The linear frequency modulation signals superimposed on the data signals are used as the training signals. By performing FRFT on the received signals and searching the peak value of the FRFT results, the receiver can realize timing synchronization and frequency offset acquisition simultaneously. Compared with the existing methods, the proposed algorithm can provide better timing synchronization performance and larger frequency offset acquisition range even under multi-path channels with low signal to noise ratio. Theoretical analysis and simulation results prove this point.
基金Project(60532030) supported by the National Natural Science Foundation of China
文摘In an orthogonal frequency division multiplexing(OFDM) system,a time and frequency domain least mean square algorithm(TF-LMS) was proposed to cancel the frequency offset(FO).TF-LMS algorithm is composed of two stages.Firstly,time domain least mean square(TD-LMS) scheme was selected to pre-cancel the frequency offset in the time domain,and then the interference induced by residual frequency offset was eliminated by the frequency domain mean square(FD-LMS) scheme in frequency domain.The results of bit error rate(BER) and quadrature phase shift keying(QPSK) constellation figures show that the performance of the proposed suppression algorithm is excellent.
基金supported by the National Natural Science Foundation of China(6137116961301108+1 种基金61071164)the Fundamental Research Funds for the Central Universities(NS2013024)
文摘The problem of channel estimation for multiple an- tenna orthogonal frequency division multiplexing （OFDM） systems subject to unknown carrier frequency offset （CFO） is addressed. Multiple signal classification （MUSIC）-Iike algorithm, which generally has been used for direction estimation or frequency estimation, is used for channel estimation in multiple antenna OFDM systems. A reduced dimensional （RD）-MUSIC based algorithm for channel estimation is proposed in multiple antenna OFDM systems with unknown CFO. The Cramer-Rao bound （CRB） of channel estimation in multiple antenna OFDM systems with unknown CFO is derived. The proposed algorithm has a superior performance of channel estimation compared with the Capon method and the least squares method.
基金supported by the National Science Fund for Distinguished Young Scholars (60725105)National"863"Program of China (2007AA01Z288)+1 种基金the sixth project of the Key Project of National Nature Science Foundation of China (60496316)Teaching Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE,the 111 Project (B08038).
文摘Carrier frequency offset （CFO） in MIMO-OFDM systems can be decoupled into two parts： fraction frequency offset （FFO） and integer frequency offset （IFO）. The problem of IFO estimation is addressed and a new IFO estimator based on the Bayesian philosophy is proposed. Also, it is shown that the Bayesian IFO estimator is optimal among all the IFO estimators. Furthermore, the Bayesian estimator can take advantage of oversampling so that better performance can be obtained. Finally, numerical results show the optimality of the Bayesian estimator and validate the theoretical analysis.
文摘A tunable dual polarization absorption-transmission-absorption(A-T-A)frequency selective absorbers(FSR)to address the issue of high insertion loss in current tunable FSRs is proposed.The lumped resistors are loaded onto the lossy layer to absorb electromagnetic waves within the absorption band.The varactor diodes are loaded onto another lossless layer to control the transmission frequency band of the FSR.Its equivalent circuit model is provided.The proposed tunable FSR can change the passband within the range of 14.5~15.5 GHz by changing the bias voltage applied to the lossless transmission layer,while maintaining insertion loss above-1.67 dB.The series resonant structure of the lossy layer generates bilateral absorption bands between 10.2~13.5 GHz and 17.2~22 GHz,with broadband reflection suppression ranging from 10.3 GHz to 22 GHz(70.7%).The prototype is manufactured,and the measured results have verified the simulation results.
基金supported by Shandong Provincial Natural Science Foundation(ZR2020MF015)Aerospace Technology Group Stability Support Project(ZY0110020009).
文摘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.
