Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like freq...Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like frequency from such signals is possible,achieving high-precision vibration parameters remains challenging.This paper proposed a novel two-stage off-grid estimation method.It leverages a unique array layout(coprime array)to obtain a regular augmented covariance matrix.Subsequently,parameters in the matrix are recovered using the sparse iterative covariance-based estimation method based on covariance fitting criteria.Finally,high-precision estimates of imprecise parameters are obtained using unconditional maximum likelihood estimation,effectively eliminating the effects of basis mismatch.Through substantial numerical and experimental validation,the proposed method demonstrates significantly higher accuracy compared to classical BTT parameter estimation methods,approaching the lower bound of unbiased estimation variance.Furthermore,due to its immunity to frequency gridding,it can track minor frequency deviations,making it more suitable for indicating blade condition.展开更多
An autoregressive long-and short-term memory(ARLSTM)model was applied to develop a real-time probabilistic slope stability estimation model for the engineered barrier system(EBS)of a near surface radioactive waste dis...An autoregressive long-and short-term memory(ARLSTM)model was applied to develop a real-time probabilistic slope stability estimation model for the engineered barrier system(EBS)of a near surface radioactive waste disposal facility.The effectiveness of the developed model was verified using actual data acquired from South Korea,including precipitation,soil moisture contents,and inclinometer time-series data.The precipitation and the factor of safety(FS)ensemble results were used as the input and output variables of the AR-LSTM model,respectively,where the FS ensemble results were calculated by the Taylor model,integrating the Mualem-van Genuchten soil water retention model with consideration of the multivariate statistics on the hydrophysical properties of the soil.The estimation accuracy of the AR-LSTM model was reasonable by showing high correlation coefficient(0.9468)and low root mean squared error(0.0070)values between the actual and estimated FS values.Moreover,a significant correlation was observed between the estimated FS ensemble results and displacement events recorded by the inclinometer sensor.All the results suggest the effectiveness of the developed model for the long-term integrity assurance of the EBS.展开更多
The accuracy of conventional time delay estimation （TDE） algorithms is limited by the sampling interval. A novel algorithm of subsample TDE suitable for widehand signals is presented to improve the accuracy. This al...The accuracy of conventional time delay estimation （TDE） algorithms is limited by the sampling interval. A novel algorithm of subsample TDE suitable for widehand signals is presented to improve the accuracy. This algorithm applies periodogram and parabolic interpolation to the cross correlation spectrum of band limited stochastic signals, and can obtain a continuous time delay estimator. Simulations are carried out to compare the performance of the proposed algorithm with that of other subsample TDE algorithms. Results show that the proposed algorithm outperforms other algorithms and reachs the Cramer-Rao lower bound （CRLB） at a high signal- to-noise ratio. For the wideband characteristic and the randomness of the transmitting signal, the proposed algo- rithm is suitable for the low probability of intercept radars.展开更多
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 Dopple...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.展开更多
Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous r...Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat.Therefore,there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield,making precise yield prediction increasingly important.This study was based on four type of indicators including meteorological,crop growth status,environmental,and drought index,from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield.Using the sparrow search al-gorithm combined with random forest(SSA-RF)under different input indicators,accuracy of winter wheat yield estimation was calcu-lated.The estimation accuracy of SSA-RF was compared with partial least squares regression(PLSR),extreme gradient boosting(XG-Boost),and random forest(RF)models.Finally,the determined optimal yield estimation method was used to predict winter wheat yield in three typical years.Following are the findings:1)the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms.The best yield estimation method is achieved by four types indicators’composition with SSA-RF)(R^(2)=0.805,RRMSE=9.9%.2)Crops growth status and environmental indicators play significant roles in wheat yield estimation,accounting for 46%and 22%of the yield importance among all indicators,respectively.3)Selecting indicators from October to April of the follow-ing year yielded the highest accuracy in winter wheat yield estimation,with an R^(2)of 0.826 and an RMSE of 9.0%.Yield estimates can be completed two months before the winter wheat harvest in June.4)The predicted performance will be slightly affected by severe drought.Compared with severe drought year(2011)(R^(2)=0.680)and normal year(2017)(R^(2)=0.790),the SSA-RF model has higher prediction accuracy for wet year(2018)(R^(2)=0.820).This study could provide an innovative approach for remote sensing estimation of winter wheat yield.yield.展开更多
The problems of time delay estimation of narrowband signals are presented. The disadvantages of the existing algorithms are analyzed, and a new narrowband time delay estimating algorithm based on correlation coefficie...The problems of time delay estimation of narrowband signals are presented. The disadvantages of the existing algorithms are analyzed, and a new narrowband time delay estimating algorithm based on correlation coefficient is proposed. The original time delay information is transfered into the delay between the autocorrelation and cross-correlation function, and the precise estimating result by wave-comparison is given. The algorithm proposed here is also compared with other algorithms and its advantages over other algorithms are proved. The theoretical analysis and simulation show the effectiveness of the proposed algorithm.展开更多
A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information ...A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.展开更多
This paper proposes a novel approach for identifying distributed dynamic loads in the time domain.Using polynomial andmodal analysis,the load is transformed intomodal space for coefficient identification.This allows t...This paper proposes a novel approach for identifying distributed dynamic loads in the time domain.Using polynomial andmodal analysis,the load is transformed intomodal space for coefficient identification.This allows the distributed dynamic load with a two-dimensional form in terms of time and space to be simultaneously identified in the form of modal force,thereby achieving dimensionality reduction.The Impulse-based Force Estimation Algorithm is proposed to identify dynamic loads in the time domain.Firstly,the algorithm establishes a recursion scheme based on convolution integral,enabling it to identify loads with a long history and rapidly changing forms over time.Secondly,the algorithm introduces moving mean and polynomial fitting to detrend,enhancing its applicability in load estimation.The aforementioned methodology successfully accomplishes the reconstruction of distributed,instead of centralized,dynamic loads on the continuum in the time domain by utilizing acceleration response.To validate the effectiveness of the method,computational and experimental verification were conducted.展开更多
A modified time domain interpolation method is proposed for orthogonal frequency division multiplexing(OFDM)systems to address the problem that time domain interpolation in the least square(LS)channel estimation metho...A modified time domain interpolation method is proposed for orthogonal frequency division multiplexing(OFDM)systems to address the problem that time domain interpolation in the least square(LS)channel estimation method based on comb-type pilots cannot choose the pilot spacing flexibly.Firstly,the estimated channel frequency response(CFR)at pilot positions in the frequency domain is obtained by LS channel estimation based on comb-type pilots,and the estimated channel impulse response(CIR)in the time domain is obtained by linear interpolation and inverse fast Fourier transform(IFFT).Secondly,the error of the estimated CIR obtained by linear interpolation is analyzed by theoretical deduction,and a method for correcting it is proposed.Finally,an estimated CFR at all subcarrier positions in the frequency domain is obtained by performing zero padding in the time domain and fast Fourier transform(FFT)on the modified CIR.The simulation results suggest that the proposed method gives similar performance to time domain interpolation,yet it does not need to meet the condition of time domain interpolation that the number of subcarriers must be an integral multiple of pilot spacing to use it.The proposed method allows for flexible pilot spacing,reducing the number of pilots and the consumption of subcarriers used for channel estimation.展开更多
Higher-order statistics based approaches and signal sparseness based approaches have emerged in recent decades to resolve the underdetermined direction-of-arrival(DOA)estimation problem.These model-based methods face ...Higher-order statistics based approaches and signal sparseness based approaches have emerged in recent decades to resolve the underdetermined direction-of-arrival(DOA)estimation problem.These model-based methods face great challenges in practical applications due to high computational complexity and dependence on ideal assumptions.This paper presents an effective DOA estimation approach based on a deep residual network(DRN)for the underdetermined case.We first extract an input feature from a new matrix calculated by stacking several covariance matrices corresponding to different time delays.We then provide the input feature to the trained DRN to construct the super resolution spectrum.The DRN learns the mapping relationship between the input feature and the spatial spectrum by training.The proposed approach is superior to existing model-based estimation methods in terms of calculation efficiency,independence of source sparseness and adaptive capacity to non-ideal conditions(e.g.,low signal to noise ratio,short bit sequence).Simulations demonstrate the validity and strong performance of the proposed algorithm on both overdetermined and underdetermined cases.展开更多
A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay ...A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay arrivals of surface-bottom reflection and bottom-surface reflection intersect at the source depth. Two hydrophones deployed vertically with a certain interval are required at least. If the receiver depths are known, the pair of time delays can be used to estimate the source depth. With the proposed method the source depth can be estimated successfully in a moderate range in the deep ocean without complicated matched-field calculations in the simulations and experiments.展开更多
The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two rec...The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two received signals is obtained and the fractional lower order cross-covariance spectrum (FLOCCS) can be approached by taking a Fourier transform for the FLOCC sequence. When the FLOCCS is treated as a sequence in the time domain, the problem of multipath time delay estimation (TDE) may be converted into one on multi-frequencies estimation or directions of arrival estimation. Accordingly, the high resolution multipath TDE can be realized with the ESPRIT technology. This idea on multipath TDE is referred to as FLOCCS-ESPRIT in this paper. Computer simulations show that this method has good performance both in a Gaussian noise and in an impulsive noise environment.展开更多
Orthogonal time frequency space(OTFS)technique, which modulates data symbols in the delayDoppler(DD) domain, presents a potential solution for supporting reliable information transmission in highmobility vehicular net...Orthogonal time frequency space(OTFS)technique, which modulates data symbols in the delayDoppler(DD) domain, presents a potential solution for supporting reliable information transmission in highmobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing(UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model(HMM). The empirical state evolution(SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm,we derive the update criterion for the hyperparameters through the expectation-maximization(EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.展开更多
In this paper,parameter estimation of linear frequency modulation(LFM)signals containing additive white Gaussian noise is studied.Because the center frequency estimation of an LFM signal is affected by the error propa...In this paper,parameter estimation of linear frequency modulation(LFM)signals containing additive white Gaussian noise is studied.Because the center frequency estimation of an LFM signal is affected by the error propagation effect,resulting in a higher signal to noise ratio(SNR)threshold,a parameter estimation method for LFM signals based on time reversal is proposed.The proposed method avoids SNR loss in the process of estimating the frequency,thus reducing the SNR threshold.The simulation results show that the threshold is reduced by 5 dB compared with the discrete polynomial transform(DPT)method,and the root-mean-square error(RMSE)of the proposed estimator is close to the Cramer-Rao lower bound(CRLB).展开更多
Although the effects of the coalescent process on sequence divergence and genealogies are well understood, the vir- tual majority of studies that use molecular sequences to estimate times of divergence among species h...Although the effects of the coalescent process on sequence divergence and genealogies are well understood, the vir- tual majority of studies that use molecular sequences to estimate times of divergence among species have failed to account for the coalescent process. Here we study the impact of ancestral population size and incomplete lineage sorting on Bayesian estimates of species divergence times under the molecular clock when the inference model ignores the coalescent process. Using a combination of mathematical analysis, computer simulations and analysis of real data, we find that the errors on estimates of times and the molecular rate can be substantial when ancestral populations are large and when there is substantial incomplete lineage sorting. For example, in a simple three-species case, we find that if the most precise fossil calibration is placed on the root of the phylogeny, the age of the internal node is overestimated, while if the most precise calibration is placed on the internal node, then the age of the root is underestimated. In both cases, the molecular rate is overestimated. Using simulations on a phylogeny of nine species, we show that substantial errors in time and rate estimates can be obtained even when dating ancient divergence events. We analyse the hominoid phylogeny and show that estimates of the neutral mutation rate obtained while ignoring the coalescent are too high. Using a coalescent-based technique to obtain geological times of divergence, we obtain estimates of the mutation rate that are within experimental estimates and we also obtain substantially older divergence times within the phylogeny [Current Zoology 61 （5）： 874-885, 2015].展开更多
Generalized cross-correlation is considered as the most straightforward time delay estimation algorithm.Depending on various weighting function,different methods were derived and a straightforward method,named phase t...Generalized cross-correlation is considered as the most straightforward time delay estimation algorithm.Depending on various weighting function,different methods were derived and a straightforward method,named phase transform(PHAT)has been widely used.PHAT is well-known for its robustness to reverberation and its sensitivity to noise,which is partly due to the fact that PHAT distributes same weights to the frequencies dominated by signal or noise.To alleviate this problem,two weighting functions are proposed in this paper.By taking a posteriori signal-to-noise ratio(SNR)into account to classify reliable and unreliable frequencies,different weights could be assigned.The first proposed weighting function borrows the idea of binary mask and distributes same weights to frequencies in same set,whereas,the second one assigns weights based on coherence function.Experiments showed the robustness of proposed methods to reverberation and noise for improving the performance of time delay estimation through various criteria.展开更多
The reconstruction control of modular self-reconfigurable spacecraft (MSRS) is addressed using an adaptive sliding mode control (ASMC) scheme based on time-delay estimation (TDE) technology. In contrast to the ground,...The reconstruction control of modular self-reconfigurable spacecraft (MSRS) is addressed using an adaptive sliding mode control (ASMC) scheme based on time-delay estimation (TDE) technology. In contrast to the ground, the base of the MSRS is floating when assembled in orbit, resulting in a strong dynamic coupling effect. A TED-based ASMC technique with exponential reaching law is designed to achieve high-precision coordinated control between the spacecraft base and the robotic arm. TDE technology is used by the controller to compensate for coupling terms and uncertainties, while ASMC can augment and improve TDE’s robustness. To suppress TDE errors and eliminate chattering, a new adaptive law is created to modify gain parameters online, ensuring quick dynamic response and high tracking accuracy. The Lyapunov approach shows that the tracking errors are uniformly ultimately bounded (UUB). Finally, the on-orbit assembly process of MSRS is simulated to validate the efficacy of the proposed control scheme. The simulation results show that the proposed control method can accurately complete the target module’s on-orbit assembly, with minimal perturbations to the spacecraft’s attitude. Meanwhile, it has a high level of robustness and can effectively eliminate chattering.展开更多
Travel times have been traditionally estimated from data collected by roadway sensors. Recently, new tech- nologies, such as cell phone tracking, license plate matching, automatic vehicle identifications and video det...Travel times have been traditionally estimated from data collected by roadway sensors. Recently, new tech- nologies, such as cell phone tracking, license plate matching, automatic vehicle identifications and video detection, are employed for this purpose. In this study, the data collected by TRANSMIT readers, Bluetooth sensors, and INRIX are assessed by comparing each to the ＂ground truth＂ travel times collected by probe vehicles carrying GPS-based naviga- tion devices. Travel times of probe vehicles traveling on the study segment of 1-287 in New Jersey were collected in 2009. Statistical measures, such as standard deviation, average absolute speed error, and speed error bias, were used to make an in-depth analysis. The accuracy of each travel time estimation method is analyzed. The data collected by Bluetooth sensors and the TRANSMIT readers seem more consistent with the ground true data, and slightly outperform the data reported by 1NRIX. This study established a procedure for analyzing the accuracy of floating car data （FCD） collected by different technologies.展开更多
Time delay estimation (TDE) is an important issue in signal processing. Conventional TDE algorithms are usually efficient under white noise environments. In this paper, a joint noise reduction and -norm minimization m...Time delay estimation (TDE) is an important issue in signal processing. Conventional TDE algorithms are usually efficient under white noise environments. In this paper, a joint noise reduction and -norm minimization method is presented to enhance TDE in colored noise. An improved subspace method for colored noise reduction is first performed. Then the time delay is estimated by using an -norm minimization method. Because the clean speech signal form the noisy signal is well extracted by noise reduction and the -norm minimization method is robust, the TDE accuracy can be enhanced. Experiment results confirm that the proposed joint estimation method obtains more accurate TDE than several conventional algorithms in colored noise, especially in the case of low signal-to-noise ratio. 展开更多
为线性分离变化时间的系统的 H 混合评价问题在这份报纸被调查，在估计的信号是状态和输入的线性联合的地方。设计目的从骚乱要求最坏的精力获得到是的评价错误不到规定水平。混合评价问题的最佳的答案是僵绳点一二播放器零和微分游戏...为线性分离变化时间的系统的 H 混合评价问题在这份报纸被调查，在估计的信号是状态和输入的线性联合的地方。设计目的从骚乱要求最坏的精力获得到是的评价错误不到规定水平。混合评价问题的最佳的答案是僵绳点一二播放器零和微分游戏。根据微分比赛途径，为混合评价问题的必要、足够的可解决的条件以一个 Riccati 微分方程的答案被提供。而且，如果可解决的条件满足，一个可能的评估者被建议。评估者被印射矩阵的一个获得矩阵和产量描绘，在后者反映在未知输入和输出评价错误之间的内部关系的地方。最后，一个数字例子被提供说明建议途径。展开更多
基金the National Natural Science Foundation of China(Nos.52105117,52222504&51875433)the Funds for Distinguished Young talent of Shaanxi Province,China(No.2019JC-04)。
文摘Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like frequency from such signals is possible,achieving high-precision vibration parameters remains challenging.This paper proposed a novel two-stage off-grid estimation method.It leverages a unique array layout(coprime array)to obtain a regular augmented covariance matrix.Subsequently,parameters in the matrix are recovered using the sparse iterative covariance-based estimation method based on covariance fitting criteria.Finally,high-precision estimates of imprecise parameters are obtained using unconditional maximum likelihood estimation,effectively eliminating the effects of basis mismatch.Through substantial numerical and experimental validation,the proposed method demonstrates significantly higher accuracy compared to classical BTT parameter estimation methods,approaching the lower bound of unbiased estimation variance.Furthermore,due to its immunity to frequency gridding,it can track minor frequency deviations,making it more suitable for indicating blade condition.
基金supported by the Radioactive Waste Management of the Korea Institute of Energy Technology Evaluation and Planning grant funded by the Korea government Ministry of Knowledge(20193210100130)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.202008980000).
文摘An autoregressive long-and short-term memory(ARLSTM)model was applied to develop a real-time probabilistic slope stability estimation model for the engineered barrier system(EBS)of a near surface radioactive waste disposal facility.The effectiveness of the developed model was verified using actual data acquired from South Korea,including precipitation,soil moisture contents,and inclinometer time-series data.The precipitation and the factor of safety(FS)ensemble results were used as the input and output variables of the AR-LSTM model,respectively,where the FS ensemble results were calculated by the Taylor model,integrating the Mualem-van Genuchten soil water retention model with consideration of the multivariate statistics on the hydrophysical properties of the soil.The estimation accuracy of the AR-LSTM model was reasonable by showing high correlation coefficient(0.9468)and low root mean squared error(0.0070)values between the actual and estimated FS values.Moreover,a significant correlation was observed between the estimated FS ensemble results and displacement events recorded by the inclinometer sensor.All the results suggest the effectiveness of the developed model for the long-term integrity assurance of the EBS.
基金Supported by the National Mobile Communications Research Laboratory Foundation (N200902)~~
文摘The accuracy of conventional time delay estimation （TDE） algorithms is limited by the sampling interval. A novel algorithm of subsample TDE suitable for widehand signals is presented to improve the accuracy. This algorithm applies periodogram and parabolic interpolation to the cross correlation spectrum of band limited stochastic signals, and can obtain a continuous time delay estimator. Simulations are carried out to compare the performance of the proposed algorithm with that of other subsample TDE algorithms. Results show that the proposed algorithm outperforms other algorithms and reachs the Cramer-Rao lower bound （CRLB） at a high signal- to-noise ratio. For the wideband characteristic and the randomness of the transmitting signal, the proposed algo- rithm is suitable for the low probability of intercept radars.
文摘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.
基金Under the auspices of National Natural Science Foundation of China(No.52079103)。
文摘Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat.Therefore,there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield,making precise yield prediction increasingly important.This study was based on four type of indicators including meteorological,crop growth status,environmental,and drought index,from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield.Using the sparrow search al-gorithm combined with random forest(SSA-RF)under different input indicators,accuracy of winter wheat yield estimation was calcu-lated.The estimation accuracy of SSA-RF was compared with partial least squares regression(PLSR),extreme gradient boosting(XG-Boost),and random forest(RF)models.Finally,the determined optimal yield estimation method was used to predict winter wheat yield in three typical years.Following are the findings:1)the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms.The best yield estimation method is achieved by four types indicators’composition with SSA-RF)(R^(2)=0.805,RRMSE=9.9%.2)Crops growth status and environmental indicators play significant roles in wheat yield estimation,accounting for 46%and 22%of the yield importance among all indicators,respectively.3)Selecting indicators from October to April of the follow-ing year yielded the highest accuracy in winter wheat yield estimation,with an R^(2)of 0.826 and an RMSE of 9.0%.Yield estimates can be completed two months before the winter wheat harvest in June.4)The predicted performance will be slightly affected by severe drought.Compared with severe drought year(2011)(R^(2)=0.680)and normal year(2017)(R^(2)=0.790),the SSA-RF model has higher prediction accuracy for wet year(2018)(R^(2)=0.820).This study could provide an innovative approach for remote sensing estimation of winter wheat yield.yield.
基金supported partly by the National Natural Science Foundation of China(6037208130570475)the Education Ministry Doctoral Degree Foundation of China(20050141025).
文摘The problems of time delay estimation of narrowband signals are presented. The disadvantages of the existing algorithms are analyzed, and a new narrowband time delay estimating algorithm based on correlation coefficient is proposed. The original time delay information is transfered into the delay between the autocorrelation and cross-correlation function, and the precise estimating result by wave-comparison is given. The algorithm proposed here is also compared with other algorithms and its advantages over other algorithms are proved. The theoretical analysis and simulation show the effectiveness of the proposed algorithm.
基金Project(D101106049710005) supported by the Beijing Science Foundation Program,ChinaProject(61104164) supported by the National Natural Science Foundation,China
文摘A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.
文摘This paper proposes a novel approach for identifying distributed dynamic loads in the time domain.Using polynomial andmodal analysis,the load is transformed intomodal space for coefficient identification.This allows the distributed dynamic load with a two-dimensional form in terms of time and space to be simultaneously identified in the form of modal force,thereby achieving dimensionality reduction.The Impulse-based Force Estimation Algorithm is proposed to identify dynamic loads in the time domain.Firstly,the algorithm establishes a recursion scheme based on convolution integral,enabling it to identify loads with a long history and rapidly changing forms over time.Secondly,the algorithm introduces moving mean and polynomial fitting to detrend,enhancing its applicability in load estimation.The aforementioned methodology successfully accomplishes the reconstruction of distributed,instead of centralized,dynamic loads on the continuum in the time domain by utilizing acceleration response.To validate the effectiveness of the method,computational and experimental verification were conducted.
基金The National Natural Science Foundation of China(No.51975117)。
文摘A modified time domain interpolation method is proposed for orthogonal frequency division multiplexing(OFDM)systems to address the problem that time domain interpolation in the least square(LS)channel estimation method based on comb-type pilots cannot choose the pilot spacing flexibly.Firstly,the estimated channel frequency response(CFR)at pilot positions in the frequency domain is obtained by LS channel estimation based on comb-type pilots,and the estimated channel impulse response(CIR)in the time domain is obtained by linear interpolation and inverse fast Fourier transform(IFFT).Secondly,the error of the estimated CIR obtained by linear interpolation is analyzed by theoretical deduction,and a method for correcting it is proposed.Finally,an estimated CFR at all subcarrier positions in the frequency domain is obtained by performing zero padding in the time domain and fast Fourier transform(FFT)on the modified CIR.The simulation results suggest that the proposed method gives similar performance to time domain interpolation,yet it does not need to meet the condition of time domain interpolation that the number of subcarriers must be an integral multiple of pilot spacing to use it.The proposed method allows for flexible pilot spacing,reducing the number of pilots and the consumption of subcarriers used for channel estimation.
基金supported by the Program for Innovative Research Groups of the Hunan Provincial Natural Science Foundation of China(2019JJ10004)。
文摘Higher-order statistics based approaches and signal sparseness based approaches have emerged in recent decades to resolve the underdetermined direction-of-arrival(DOA)estimation problem.These model-based methods face great challenges in practical applications due to high computational complexity and dependence on ideal assumptions.This paper presents an effective DOA estimation approach based on a deep residual network(DRN)for the underdetermined case.We first extract an input feature from a new matrix calculated by stacking several covariance matrices corresponding to different time delays.We then provide the input feature to the trained DRN to construct the super resolution spectrum.The DRN learns the mapping relationship between the input feature and the spatial spectrum by training.The proposed approach is superior to existing model-based estimation methods in terms of calculation efficiency,independence of source sparseness and adaptive capacity to non-ideal conditions(e.g.,low signal to noise ratio,short bit sequence).Simulations demonstrate the validity and strong performance of the proposed algorithm on both overdetermined and underdetermined cases.
基金Supported by the National Natural Science Foundation of China under Grant No 11174235
文摘A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay arrivals of surface-bottom reflection and bottom-surface reflection intersect at the source depth. Two hydrophones deployed vertically with a certain interval are required at least. If the receiver depths are known, the pair of time delays can be used to estimate the source depth. With the proposed method the source depth can be estimated successfully in a moderate range in the deep ocean without complicated matched-field calculations in the simulations and experiments.
基金Projects 60372081, 30170259 and 30570475 supported by the National Natural Science Foundation of China, VSN-2005-01 the Opened Foundation of National Key-Lab of Vibration, Impact and Noise, 80523+1 种基金the Science Foundation of Hainan Province and Hj200501 the Foundation of Education Department of Hainan Province
文摘The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two received signals is obtained and the fractional lower order cross-covariance spectrum (FLOCCS) can be approached by taking a Fourier transform for the FLOCC sequence. When the FLOCCS is treated as a sequence in the time domain, the problem of multipath time delay estimation (TDE) may be converted into one on multi-frequencies estimation or directions of arrival estimation. Accordingly, the high resolution multipath TDE can be realized with the ESPRIT technology. This idea on multipath TDE is referred to as FLOCCS-ESPRIT in this paper. Computer simulations show that this method has good performance both in a Gaussian noise and in an impulsive noise environment.
基金supported by the Key Scientific Research Project in Colleges and Universities of Henan Province of China(Grant Nos.21A510003)Science and the Key Science and Technology Research Project of Henan Province of China(Grant Nos.222102210053)。
文摘Orthogonal time frequency space(OTFS)technique, which modulates data symbols in the delayDoppler(DD) domain, presents a potential solution for supporting reliable information transmission in highmobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing(UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model(HMM). The empirical state evolution(SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm,we derive the update criterion for the hyperparameters through the expectation-maximization(EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.
基金supported by the Regional Joint Fund for Basic and Applied Basic Research of Guangdong Province(2019B1515120009)the Defense Basic Scientific Research Program(61424132005).
文摘In this paper,parameter estimation of linear frequency modulation(LFM)signals containing additive white Gaussian noise is studied.Because the center frequency estimation of an LFM signal is affected by the error propagation effect,resulting in a higher signal to noise ratio(SNR)threshold,a parameter estimation method for LFM signals based on time reversal is proposed.The proposed method avoids SNR loss in the process of estimating the frequency,thus reducing the SNR threshold.The simulation results show that the threshold is reduced by 5 dB compared with the discrete polynomial transform(DPT)method,and the root-mean-square error(RMSE)of the proposed estimator is close to the Cramer-Rao lower bound(CRLB).
文摘Although the effects of the coalescent process on sequence divergence and genealogies are well understood, the vir- tual majority of studies that use molecular sequences to estimate times of divergence among species have failed to account for the coalescent process. Here we study the impact of ancestral population size and incomplete lineage sorting on Bayesian estimates of species divergence times under the molecular clock when the inference model ignores the coalescent process. Using a combination of mathematical analysis, computer simulations and analysis of real data, we find that the errors on estimates of times and the molecular rate can be substantial when ancestral populations are large and when there is substantial incomplete lineage sorting. For example, in a simple three-species case, we find that if the most precise fossil calibration is placed on the root of the phylogeny, the age of the internal node is overestimated, while if the most precise calibration is placed on the internal node, then the age of the root is underestimated. In both cases, the molecular rate is overestimated. Using simulations on a phylogeny of nine species, we show that substantial errors in time and rate estimates can be obtained even when dating ancient divergence events. We analyse the hominoid phylogeny and show that estimates of the neutral mutation rate obtained while ignoring the coalescent are too high. Using a coalescent-based technique to obtain geological times of divergence, we obtain estimates of the mutation rate that are within experimental estimates and we also obtain substantially older divergence times within the phylogeny [Current Zoology 61 （5）： 874-885, 2015].
基金supported by the National Natural Science Foundation of China(Grant No.61831019).
文摘Generalized cross-correlation is considered as the most straightforward time delay estimation algorithm.Depending on various weighting function,different methods were derived and a straightforward method,named phase transform(PHAT)has been widely used.PHAT is well-known for its robustness to reverberation and its sensitivity to noise,which is partly due to the fact that PHAT distributes same weights to the frequencies dominated by signal or noise.To alleviate this problem,two weighting functions are proposed in this paper.By taking a posteriori signal-to-noise ratio(SNR)into account to classify reliable and unreliable frequencies,different weights could be assigned.The first proposed weighting function borrows the idea of binary mask and distributes same weights to frequencies in same set,whereas,the second one assigns weights based on coherence function.Experiments showed the robustness of proposed methods to reverberation and noise for improving the performance of time delay estimation through various criteria.
基金This study was supported by the National Defense Science and Technology Innovation Zone of China(Grant No.00205501).
文摘The reconstruction control of modular self-reconfigurable spacecraft (MSRS) is addressed using an adaptive sliding mode control (ASMC) scheme based on time-delay estimation (TDE) technology. In contrast to the ground, the base of the MSRS is floating when assembled in orbit, resulting in a strong dynamic coupling effect. A TED-based ASMC technique with exponential reaching law is designed to achieve high-precision coordinated control between the spacecraft base and the robotic arm. TDE technology is used by the controller to compensate for coupling terms and uncertainties, while ASMC can augment and improve TDE’s robustness. To suppress TDE errors and eliminate chattering, a new adaptive law is created to modify gain parameters online, ensuring quick dynamic response and high tracking accuracy. The Lyapunov approach shows that the tracking errors are uniformly ultimately bounded (UUB). Finally, the on-orbit assembly process of MSRS is simulated to validate the efficacy of the proposed control scheme. The simulation results show that the proposed control method can accurately complete the target module’s on-orbit assembly, with minimal perturbations to the spacecraft’s attitude. Meanwhile, it has a high level of robustness and can effectively eliminate chattering.
文摘Travel times have been traditionally estimated from data collected by roadway sensors. Recently, new tech- nologies, such as cell phone tracking, license plate matching, automatic vehicle identifications and video detection, are employed for this purpose. In this study, the data collected by TRANSMIT readers, Bluetooth sensors, and INRIX are assessed by comparing each to the ＂ground truth＂ travel times collected by probe vehicles carrying GPS-based naviga- tion devices. Travel times of probe vehicles traveling on the study segment of 1-287 in New Jersey were collected in 2009. Statistical measures, such as standard deviation, average absolute speed error, and speed error bias, were used to make an in-depth analysis. The accuracy of each travel time estimation method is analyzed. The data collected by Bluetooth sensors and the TRANSMIT readers seem more consistent with the ground true data, and slightly outperform the data reported by 1NRIX. This study established a procedure for analyzing the accuracy of floating car data （FCD） collected by different technologies.
文摘Time delay estimation (TDE) is an important issue in signal processing. Conventional TDE algorithms are usually efficient under white noise environments. In this paper, a joint noise reduction and -norm minimization method is presented to enhance TDE in colored noise. An improved subspace method for colored noise reduction is first performed. Then the time delay is estimated by using an -norm minimization method. Because the clean speech signal form the noisy signal is well extracted by noise reduction and the -norm minimization method is robust, the TDE accuracy can be enhanced. Experiment results confirm that the proposed joint estimation method obtains more accurate TDE than several conventional algorithms in colored noise, especially in the case of low signal-to-noise ratio.
基金Supported by NationalNatural Science Foundation of China （60774068, 60574050） and China Postdoctor Science Foundation （20070421064）
文摘为线性分离变化时间的系统的 H 混合评价问题在这份报纸被调查，在估计的信号是状态和输入的线性联合的地方。设计目的从骚乱要求最坏的精力获得到是的评价错误不到规定水平。混合评价问题的最佳的答案是僵绳点一二播放器零和微分游戏。根据微分比赛途径，为混合评价问题的必要、足够的可解决的条件以一个 Riccati 微分方程的答案被提供。而且，如果可解决的条件满足，一个可能的评估者被建议。评估者被印射矩阵的一个获得矩阵和产量描绘，在后者反映在未知输入和输出评价错误之间的内部关系的地方。最后，一个数字例子被提供说明建议途径。
