The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a ...The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is huge.To solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this paper.Firstly,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very small.In other words,the accuracies of estimation in these directions are very low.Namely,the search dimension can be reduced,which in turn greatly reduces the computational load.Then,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of distortion.Finally,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity estimation.The experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.展开更多
Quantum metrology provides a fundamental limit on the precision of multi-parameter estimation,called the Heisenberg limit,which has been achieved in noiseless quantum systems.However,for systems subject to noises,it i...Quantum metrology provides a fundamental limit on the precision of multi-parameter estimation,called the Heisenberg limit,which has been achieved in noiseless quantum systems.However,for systems subject to noises,it is hard to achieve this limit since noises are inclined to destroy quantum coherence and entanglement.In this paper,a combined control scheme with feedback and quantum error correction(QEC)is proposed to achieve the Heisenberg limit in the presence of spontaneous emission,where the feedback control is used to protect a stabilizer code space containing an optimal probe state and an additional control is applied to eliminate the measurement incompatibility among three parameters.Although an ancilla system is necessary for the preparation of the optimal probe state,our scheme does not require the ancilla system to be noiseless.In addition,the control scheme in this paper has a low-dimensional code space.For the three components of a magnetic field,it can achieve the highest estimation precision with only a 2-dimensional code space,while at least a4-dimensional code space is required in the common optimal error correction protocols.展开更多
In this paper,we focus on the problem of joint estimation of DOA,power and polarization angle from sparse reconstruction perspective with array gain-phase errors,where a partly calibrated cocentered orthogonal loop an...In this paper,we focus on the problem of joint estimation of DOA,power and polarization angle from sparse reconstruction perspective with array gain-phase errors,where a partly calibrated cocentered orthogonal loop and dipole(COLD)array is utilized.In detailed implementations,we first combine the output of loop and dipole in second-order statistics domain to receive the source signals completely,and then we use continuous multiplication operator to achieve gain-phase errors calibration.After compensating the gain-phase errors,we construct a log-penalty-based optimization problem to approximate`0 norm and further exploit difference of convex(DC)functions decomposition to achieve DOA.With the aid of the estimated DOAs,the power and polarization angle estimation are obtained by the least squares(LS)method.By conducting numerical simulations,we show the effectiveness and superiorities of the proposed method.展开更多
In order to study the reliability of the empirical estimation of joint shear strength by the JRC（joint roughness coefficient）-JCS（joint compressive strength） model,natural rock joints of dif-ferent lithologic char...In order to study the reliability of the empirical estimation of joint shear strength by the JRC（joint roughness coefficient）-JCS（joint compressive strength） model,natural rock joints of dif-ferent lithologic characteristics and different sizes were selected as samples,and their shear strengths under dry and saturated conditions were measured by direct shear test and compared to those esti-mated by the JRC-JCS model.Comparison results show that for natural rock joints with joint surfaces closely matched,the average relative error of joint shear strength between empirical estimation and direct shear test is 9.9%;the reliability of the empirical estimation of joint shear strength by the JRC-JCS model is good under both dry and saturated conditions if the JRC is determined accounting for directional statistical measurements,scale effect and surface smoothing during shearing.However,for natural rock joints with joint surfaces mismatched,the average relative error of joint shear strength between empirical estimation and direct shear test is 39.9%;the reliability of empirical estimation of joint shear strength by the JRC-JCS model is questionable under both dry and saturated conditions.展开更多
In this paper,we propose a joint channel estimation and symbol detection(JCESD)algorithm relying on message-passing algorithms(MPA)for orthogonal frequency division multiple access(OFDMA)systems.The channel estimation...In this paper,we propose a joint channel estimation and symbol detection(JCESD)algorithm relying on message-passing algorithms(MPA)for orthogonal frequency division multiple access(OFDMA)systems.The channel estimation and symbol detection leverage the framework of expectation propagation(EP)and belief propagation(BP)with the aid of Gaussian approximation,respectively.Furthermore,to reduce the computation complexity involved in channel estimation,the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula.Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%,compared with the traditional linear minimum mean square error(LMMSE)algorithm,and can approach to the bit error rate(BER)performance bound of perfectly known channel state information within 0.1 dB.展开更多
A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conven...A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conventional CS-based methods where the joint spatial-temporal parameters are characterized in one large scale matrix,three smaller scale matrices with independent azimuth,elevation and Doppler frequency are introduced adopting a separable observation model.Afterwards,the estimation is achieved by L1-norm minimization and the Bayesian CS algorithm.In addition,under the L-shaped array topology,the azimuth and elevation are separated yet coupled to the same radial Doppler frequency.Hence,the pair matching problem is solved with the aid of the radial Doppler frequency.Finally,numerical simulations corroborate the feasibility and validity of the proposed algorithm.展开更多
The optimal estimation performance of target parameters is studied. First, the general form of Cramer-Rao bound （CRB） for joint estimation of target location and velocity is derived for coherent multiple input multi...The optimal estimation performance of target parameters is studied. First, the general form of Cramer-Rao bound （CRB） for joint estimation of target location and velocity is derived for coherent multiple input multiple output （MIMO） radars. To gain some insight into the behavior of the CRB, the CRB with a set of given orthogonal waveforms is studied as a specific case. Second, a maximum likelihood （ML） estimation algorithm is proposed. The mean square error （MSE） of the ML estimation of target location and velocity is obtained by Monte Carlo simulation and it approaches CRB in the high signal-to-noise ratio （SNR） region.展开更多
The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary r...The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary relationship and the design of highspeed pantographs.Good pantograph-catenary coupling quality is the essential condition to ensure safe and efficient operation of high-speed train,stable and reliable current collection,and reduction in the wear of contact wires and pantograph contact strips.Among them,the dynamic parameters of high-speed pantographs are crucial to pantograph-catenary coupling quality.With the reduction of the standard deviation of the pantograph-catenary contact force as the optimization goal,multi-parameter joint optimization designs for the high-speed pantograph with two contact strips at multiple running speeds are proposed.Moreover,combining the sensitivity analysis at the optimal solutions,with the parameters and characteristics of in-service DSA380 highspeed pantograph,the optimization proposal of DSA380 was given.展开更多
The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-...The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-MUSIC) algorithm is proposed.Conventional MUSIC algorithm for joint DOA and Doppler frequency estimation requires a large computational cost due to the two dimensional (2D) spectral peak searching.Aiming at this shortcoming,the proposed CE-MUSIC algorithm firstly uses a reduced-dimension transformation to reduce the subspace dimension and then obtains the estimates of DOA and Doppler frequency with only one-dimensional (1D) search.The proposed CE-MUSIC algorithm has much lower computational complexity and very close estimation performance when compared to conventional 2D-MUSIC algorithm.Furthermore,it outperforms estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm.Meanwhile,the mean squared error (MSE) and Cramer-Rao bound (CRB) of joint DOA and Doppler frequency estimation are derived.Detailed simulation results illustrate the validity and improvement of the proposed algorithm.展开更多
Effectiveness evaluation of the joint operation system is an important basis for the demonstration and development of weapon equipment.With the consideration that existing models of system effectiveness evaluation sel...Effectiveness evaluation of the joint operation system is an important basis for the demonstration and development of weapon equipment.With the consideration that existing models of system effectiveness evaluation seldom describe the structural relationship among equipment clearly as well as reflect the dynamic,the analog-to-digital converter-graphical evaluation and review technique(ADC-GERT)network parameter estimation model is proposed based on the ADC model and the joint operation system structure.Firstly,analysis of the joint operation system structure and operation process is conducted to build the GERT network,where equipment subsystems are nodes and activities are directed arches.Then the mission effectiveness of equipment subsystems is calculated by the ADC model.The probability transfer parameters are modified by the mission effectiveness of equipment subsystems based on the Bayesian theorem,with the ADC-GERT network parameter estimation model constructed.Finally,a case study is used to validate the efficiency and dynamic of the ADC-GERT network parameter estimation model.展开更多
This paper investigates the problem of synchronization for offset quadrature amplitude modulation based orthogonal frequency division multiplexing(OFDM/OQAM) systems based on the genetic algorithm. In order to increas...This paper investigates the problem of synchronization for offset quadrature amplitude modulation based orthogonal frequency division multiplexing(OFDM/OQAM) systems based on the genetic algorithm. In order to increase the spectrum efficiency,an improved preamble structure without guard symbols is derived at first. On this basis, instead of deriving the log likelihood function of power spectral density, joint estimation of the symbol timing offset and carrier frequency offset based on the preamble proposed is formulated into a bivariate optimization problem. After that, an improved genetic algorithm is used to find its global optimum solution. Conclusions can be drawn from simulation results that the proposed method has advantages in the joint estimation of synchronization.展开更多
In most literature about joint direction of arrival（DOA） and polarization estimation, the case that sources possess different power levels is seldom discussed. However, this case exists widely in practical applicati...In most literature about joint direction of arrival（DOA） and polarization estimation, the case that sources possess different power levels is seldom discussed. However, this case exists widely in practical applications, especially in passive radar systems. In this paper, we propose a joint DOA and polarization estimation method for unequal power sources based on the reconstructed noise subspace. The invariance property of noise subspace（IPNS） to power of sources has been proved an effective method to estimate DOA of unequal power sources. We develop the IPNS method for joint DOA and polarization estimation based on a dual polarized array. Moreover, we propose an improved IPNS method based on the reconstructed noise subspace, which has higher resolution probability than the IPNS method. It is theoretically proved that the IPNS to power of sources is still valid when the eigenvalues of the noise subspace are changed artificially. Simulation results show that the resolution probability of the proposed method is enhanced compared with the methods based on the IPNS and the polarimetric multiple signal classification（MUSIC） method. Meanwhile, the proposed method has approximately the same estimation accuracy as the IPNS method for the weak source.展开更多
Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in...Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.展开更多
A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE...A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE）- based space-alternating generalized expectation-maximization （SAGE） algorithm. In the proposed algorithm, every sub-frame of the MIMO-OFDM system is divided into some OFDM sub-blocks and the LMMSE-based SAGE algorithm in each sub-block is used. At the head of each sub-flame, we insert training symbols which are used in the initial estimation at the beginning. Channel estimation of the previous sub-block is applied to the initial estimation in the current sub-block by the maximum-likelihood （ML） detection to update channel estimatjon and data detection by iteration until converge. Then all the sub-blocks can be finished in turn. Simulation results show that the proposed algorithm can improve the bit error rate （BER） performance.展开更多
Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-b...Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-bydetection frameworks for either bottom-up or top-down approaches,requiring retraining to accommodate diverse animal appearances.This study introduces InteBOMB,an integrated workflow that enhances top-down approaches by incorporating generic object tracking,eliminating the need for prior knowledge of target animals while maintaining broad generalizability.InteBOMB includes two key strategies for tracking and segmentation in laboratory environments and two techniques for pose estimation in natural settings.The“background enhancement”strategy optimizesforeground-backgroundcontrastiveloss,generating more discriminative correlation maps.The“online proofreading”strategy stores human-in-the-loop long-term memory and dynamic short-term memory,enabling adaptive updates to object visual features.The“automated labeling suggestion”technique reuses the visual features saved during tracking to identify representative frames for training set labeling.Additionally,the“joint behavior analysis”technique integrates these features with multimodal data,expanding the latent space for behavior classification and clustering.To evaluate the framework,six datasets of mice and six datasets of nonhuman primates were compiled,covering laboratory and natural scenes.Benchmarking results demonstrated a24%improvement in zero-shot generic tracking and a 21%enhancement in joint latent space performance across datasets,highlighting the effectiveness of this approach in robust,generalizable behavior analysis.展开更多
Joint power control has advantages of multi-user detection and power control; and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estim...Joint power control has advantages of multi-user detection and power control; and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system was designed. Simulation results show that the algorithm can control the power not only quickly but also precisely with a time change. The method is useful for increasing system capacity.展开更多
It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but th...It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the method.In this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle targets.The compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target height.The algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient error.Fi-nally,the experiment and simulation results demonstrate the validity of the proposed method.展开更多
Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a mult...Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.展开更多
We propose a scheme to realize two-parameter estimation via Bose–Einstein condensates confined in a symmetric triple-well potential.The three-mode NOON state is prepared adiabatically as the initial state.The two par...We propose a scheme to realize two-parameter estimation via Bose–Einstein condensates confined in a symmetric triple-well potential.The three-mode NOON state is prepared adiabatically as the initial state.The two parameters to be estimated are the phase differences between the wells.The sensitivity of this estimation scheme is studied by comparing quantum and classical Fisher information matrices.As a result,we find an optimal particle number measurement method.Moreover,the precision of this estimation scheme means that the Heisenberg scaling behaves under the optimal measurement.展开更多
Estimation of construction parameters is crucial for optimizing tunnel construction schedule.Due to the influence of routine activities and occasional risk events,these parameters are usually correlated and imbalanced...Estimation of construction parameters is crucial for optimizing tunnel construction schedule.Due to the influence of routine activities and occasional risk events,these parameters are usually correlated and imbalanced.To solve this issue,an improved bidirectional generative adversarial network(BiGAN)model with a joint discriminator structure and zero-centered gradient penalty(0-GP)is proposed.In this model,in order to improve the capability of original BiGAN in learning imbalanced parameters,the joint discriminator separately discriminates the routine activities and risk event durations to balance their influence weights.Then,the self-attention mechanism is embedded so that the discriminator can pay more attention to the imbalanced parameters.Finally,the 0-GP is adapted for the loss of the discrimi-nator to improve its convergence and stability.A case study of a tunnel in China shows that the improved BiGAN can obtain parameter estimates consistent with the classical Gauss mixture model,without the need of tedious and complex correlation analysis.The proposed joint discriminator can increase the ability of BiGAN in estimating imbalanced construction parameters,and the 0-GP can ensure the stability and convergence of the model.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.61873196,62373030,61772187)the Innovation Program for Quantum Science and Technology(No.2021ZD0303400)。
文摘The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is huge.To solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this paper.Firstly,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very small.In other words,the accuracies of estimation in these directions are very low.Namely,the search dimension can be reduced,which in turn greatly reduces the computational load.Then,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of distortion.Finally,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity estimation.The experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.
基金Project supported by the National Natural Science Foundation of China(Grant No.61873251)。
文摘Quantum metrology provides a fundamental limit on the precision of multi-parameter estimation,called the Heisenberg limit,which has been achieved in noiseless quantum systems.However,for systems subject to noises,it is hard to achieve this limit since noises are inclined to destroy quantum coherence and entanglement.In this paper,a combined control scheme with feedback and quantum error correction(QEC)is proposed to achieve the Heisenberg limit in the presence of spontaneous emission,where the feedback control is used to protect a stabilizer code space containing an optimal probe state and an additional control is applied to eliminate the measurement incompatibility among three parameters.Although an ancilla system is necessary for the preparation of the optimal probe state,our scheme does not require the ancilla system to be noiseless.In addition,the control scheme in this paper has a low-dimensional code space.For the three components of a magnetic field,it can achieve the highest estimation precision with only a 2-dimensional code space,while at least a4-dimensional code space is required in the common optimal error correction protocols.
基金the National Natural Science Foundation of China under Grant 61171137.
文摘In this paper,we focus on the problem of joint estimation of DOA,power and polarization angle from sparse reconstruction perspective with array gain-phase errors,where a partly calibrated cocentered orthogonal loop and dipole(COLD)array is utilized.In detailed implementations,we first combine the output of loop and dipole in second-order statistics domain to receive the source signals completely,and then we use continuous multiplication operator to achieve gain-phase errors calibration.After compensating the gain-phase errors,we construct a log-penalty-based optimization problem to approximate`0 norm and further exploit difference of convex(DC)functions decomposition to achieve DOA.With the aid of the estimated DOAs,the power and polarization angle estimation are obtained by the least squares(LS)method.By conducting numerical simulations,we show the effectiveness and superiorities of the proposed method.
基金supported by the National Natural Science Foundation of China (Nos. 40672186, 50809059)the Natural Science Foundation of Zhejiang Province (No. Y505008), China
文摘In order to study the reliability of the empirical estimation of joint shear strength by the JRC（joint roughness coefficient）-JCS（joint compressive strength） model,natural rock joints of dif-ferent lithologic characteristics and different sizes were selected as samples,and their shear strengths under dry and saturated conditions were measured by direct shear test and compared to those esti-mated by the JRC-JCS model.Comparison results show that for natural rock joints with joint surfaces closely matched,the average relative error of joint shear strength between empirical estimation and direct shear test is 9.9%;the reliability of the empirical estimation of joint shear strength by the JRC-JCS model is good under both dry and saturated conditions if the JRC is determined accounting for directional statistical measurements,scale effect and surface smoothing during shearing.However,for natural rock joints with joint surfaces mismatched,the average relative error of joint shear strength between empirical estimation and direct shear test is 39.9%;the reliability of empirical estimation of joint shear strength by the JRC-JCS model is questionable under both dry and saturated conditions.
文摘In this paper,we propose a joint channel estimation and symbol detection(JCESD)algorithm relying on message-passing algorithms(MPA)for orthogonal frequency division multiple access(OFDMA)systems.The channel estimation and symbol detection leverage the framework of expectation propagation(EP)and belief propagation(BP)with the aid of Gaussian approximation,respectively.Furthermore,to reduce the computation complexity involved in channel estimation,the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula.Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%,compared with the traditional linear minimum mean square error(LMMSE)algorithm,and can approach to the bit error rate(BER)performance bound of perfectly known channel state information within 0.1 dB.
文摘A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conventional CS-based methods where the joint spatial-temporal parameters are characterized in one large scale matrix,three smaller scale matrices with independent azimuth,elevation and Doppler frequency are introduced adopting a separable observation model.Afterwards,the estimation is achieved by L1-norm minimization and the Bayesian CS algorithm.In addition,under the L-shaped array topology,the azimuth and elevation are separated yet coupled to the same radial Doppler frequency.Hence,the pair matching problem is solved with the aid of the radial Doppler frequency.Finally,numerical simulations corroborate the feasibility and validity of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(61171120)the Key National Ministry Foundation of China(9140A07020212JW0101)the Foundation of Tsinghua University(20101081772)
文摘The optimal estimation performance of target parameters is studied. First, the general form of Cramer-Rao bound （CRB） for joint estimation of target location and velocity is derived for coherent multiple input multiple output （MIMO） radars. To gain some insight into the behavior of the CRB, the CRB with a set of given orthogonal waveforms is studied as a specific case. Second, a maximum likelihood （ML） estimation algorithm is proposed. The mean square error （MSE） of the ML estimation of target location and velocity is obtained by Monte Carlo simulation and it approaches CRB in the high signal-to-noise ratio （SNR） region.
基金the National Natural Science Foundation of China(Grant No.11672297)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB22020200).
文摘The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary relationship and the design of highspeed pantographs.Good pantograph-catenary coupling quality is the essential condition to ensure safe and efficient operation of high-speed train,stable and reliable current collection,and reduction in the wear of contact wires and pantograph contact strips.Among them,the dynamic parameters of high-speed pantographs are crucial to pantograph-catenary coupling quality.With the reduction of the standard deviation of the pantograph-catenary contact force as the optimization goal,multi-parameter joint optimization designs for the high-speed pantograph with two contact strips at multiple running speeds are proposed.Moreover,combining the sensitivity analysis at the optimal solutions,with the parameters and characteristics of in-service DSA380 highspeed pantograph,the optimization proposal of DSA380 was given.
基金supported in part by the Funding for Outstanding Doctoral Dissertation in NUAA (No.BCXJ1503)the Funding of Jiangsu Innovation Program for Graduate Education(No.KYLX15_0281)the Fundamental Research Funds for the Central Universities
文摘The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-MUSIC) algorithm is proposed.Conventional MUSIC algorithm for joint DOA and Doppler frequency estimation requires a large computational cost due to the two dimensional (2D) spectral peak searching.Aiming at this shortcoming,the proposed CE-MUSIC algorithm firstly uses a reduced-dimension transformation to reduce the subspace dimension and then obtains the estimates of DOA and Doppler frequency with only one-dimensional (1D) search.The proposed CE-MUSIC algorithm has much lower computational complexity and very close estimation performance when compared to conventional 2D-MUSIC algorithm.Furthermore,it outperforms estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm.Meanwhile,the mean squared error (MSE) and Cramer-Rao bound (CRB) of joint DOA and Doppler frequency estimation are derived.Detailed simulation results illustrate the validity and improvement of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(72071111,71801127,71671091)the NSFC and the UK Royal Society joint project(71811530338)+2 种基金the Special Postdoctoral Fund of China(2019TQ0150)the Fundamental Research Funds for the Central Universities of China(NC2019003)the Intelligence Introduction Base of the Ministry of Science and Technology(G20190010178)。
文摘Effectiveness evaluation of the joint operation system is an important basis for the demonstration and development of weapon equipment.With the consideration that existing models of system effectiveness evaluation seldom describe the structural relationship among equipment clearly as well as reflect the dynamic,the analog-to-digital converter-graphical evaluation and review technique(ADC-GERT)network parameter estimation model is proposed based on the ADC model and the joint operation system structure.Firstly,analysis of the joint operation system structure and operation process is conducted to build the GERT network,where equipment subsystems are nodes and activities are directed arches.Then the mission effectiveness of equipment subsystems is calculated by the ADC model.The probability transfer parameters are modified by the mission effectiveness of equipment subsystems based on the Bayesian theorem,with the ADC-GERT network parameter estimation model constructed.Finally,a case study is used to validate the efficiency and dynamic of the ADC-GERT network parameter estimation model.
基金supported by the National Natural Science Foundation of China(61671468)。
文摘This paper investigates the problem of synchronization for offset quadrature amplitude modulation based orthogonal frequency division multiplexing(OFDM/OQAM) systems based on the genetic algorithm. In order to increase the spectrum efficiency,an improved preamble structure without guard symbols is derived at first. On this basis, instead of deriving the log likelihood function of power spectral density, joint estimation of the symbol timing offset and carrier frequency offset based on the preamble proposed is formulated into a bivariate optimization problem. After that, an improved genetic algorithm is used to find its global optimum solution. Conclusions can be drawn from simulation results that the proposed method has advantages in the joint estimation of synchronization.
基金supported by the National Natural Science Foundation of China(61501142)the China Postdoctoral Science Foundation(2015M571414)+3 种基金the Fundamental Research Funds for the Central Universities(HIT.NSRIF.2016102)Shandong Provincial Natural Science Foundation(ZR2014FQ003)the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology(HIT.NSRIF 2013130HIT(WH)XBQD 201022)
文摘In most literature about joint direction of arrival（DOA） and polarization estimation, the case that sources possess different power levels is seldom discussed. However, this case exists widely in practical applications, especially in passive radar systems. In this paper, we propose a joint DOA and polarization estimation method for unequal power sources based on the reconstructed noise subspace. The invariance property of noise subspace（IPNS） to power of sources has been proved an effective method to estimate DOA of unequal power sources. We develop the IPNS method for joint DOA and polarization estimation based on a dual polarized array. Moreover, we propose an improved IPNS method based on the reconstructed noise subspace, which has higher resolution probability than the IPNS method. It is theoretically proved that the IPNS to power of sources is still valid when the eigenvalues of the noise subspace are changed artificially. Simulation results show that the resolution probability of the proposed method is enhanced compared with the methods based on the IPNS and the polarimetric multiple signal classification（MUSIC） method. Meanwhile, the proposed method has approximately the same estimation accuracy as the IPNS method for the weak source.
基金supported by the National Natural Science Foundation of China(Grant No.12075323)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300702).
文摘Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.
基金Supported by the National Natural Science Foundation of China （No. 61001105）, the National Science and Technology Major Projects （No. 2011ZX03001- 007- 03） and Beijing Natural Science Foundation （No. 4102043）.
文摘A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE）- based space-alternating generalized expectation-maximization （SAGE） algorithm. In the proposed algorithm, every sub-frame of the MIMO-OFDM system is divided into some OFDM sub-blocks and the LMMSE-based SAGE algorithm in each sub-block is used. At the head of each sub-flame, we insert training symbols which are used in the initial estimation at the beginning. Channel estimation of the previous sub-block is applied to the initial estimation in the current sub-block by the maximum-likelihood （ML） detection to update channel estimatjon and data detection by iteration until converge. Then all the sub-blocks can be finished in turn. Simulation results show that the proposed algorithm can improve the bit error rate （BER） performance.
基金supported by the STI 2030-Major Projects(2022ZD0211900,2022ZD0211902)STI 2030-Major Projects(2021ZD0204500,2021ZD0204503)+1 种基金National Natural Science Foundation of China(32171461)National Key Research and Development Program of China(2023YFC3208303)。
文摘Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-bydetection frameworks for either bottom-up or top-down approaches,requiring retraining to accommodate diverse animal appearances.This study introduces InteBOMB,an integrated workflow that enhances top-down approaches by incorporating generic object tracking,eliminating the need for prior knowledge of target animals while maintaining broad generalizability.InteBOMB includes two key strategies for tracking and segmentation in laboratory environments and two techniques for pose estimation in natural settings.The“background enhancement”strategy optimizesforeground-backgroundcontrastiveloss,generating more discriminative correlation maps.The“online proofreading”strategy stores human-in-the-loop long-term memory and dynamic short-term memory,enabling adaptive updates to object visual features.The“automated labeling suggestion”technique reuses the visual features saved during tracking to identify representative frames for training set labeling.Additionally,the“joint behavior analysis”technique integrates these features with multimodal data,expanding the latent space for behavior classification and clustering.To evaluate the framework,six datasets of mice and six datasets of nonhuman primates were compiled,covering laboratory and natural scenes.Benchmarking results demonstrated a24%improvement in zero-shot generic tracking and a 21%enhancement in joint latent space performance across datasets,highlighting the effectiveness of this approach in robust,generalizable behavior analysis.
文摘Joint power control has advantages of multi-user detection and power control; and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system was designed. Simulation results show that the algorithm can control the power not only quickly but also precisely with a time change. The method is useful for increasing system capacity.
基金supported by the National Natural Science Foundation of China(61771367)the Science and Technology on Communication Networks Laboratory(6142104190204).
文摘It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the method.In this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle targets.The compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target height.The algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient error.Fi-nally,the experiment and simulation results demonstrate the validity of the proposed method.
基金supported by National Key R&D Program of China(Grant No.2022YFC3003903)the S&T Program of Hebei(Grant No.19275408D),the Key-Area Research and Development Program of Guangdong Province(Grant No.2020B1111200001)+1 种基金the Key Project of Monitoring,Early Warning and Prevention of Major Natural Disasters of China(Grant No.2019YFC1510304)the Joint Fund of Key Laboratory of Atmosphere Sounding,CMA,and the Research Centre on Meteorological Observation Engineering Technology,CMA(Grant No.U2021Z05).
文摘Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.
基金supported by the National Natural Science Foundation of China(NSFC)(Grant Nos.12088101,11725417,and U1930403)Science Challenge Project(Grant No.TZ2018005)。
文摘We propose a scheme to realize two-parameter estimation via Bose–Einstein condensates confined in a symmetric triple-well potential.The three-mode NOON state is prepared adiabatically as the initial state.The two parameters to be estimated are the phase differences between the wells.The sensitivity of this estimation scheme is studied by comparing quantum and classical Fisher information matrices.As a result,we find an optimal particle number measurement method.Moreover,the precision of this estimation scheme means that the Heisenberg scaling behaves under the optimal measurement.
基金supported by National Natural Science Foundation of China(Grant Nos.52279137,52009090).
文摘Estimation of construction parameters is crucial for optimizing tunnel construction schedule.Due to the influence of routine activities and occasional risk events,these parameters are usually correlated and imbalanced.To solve this issue,an improved bidirectional generative adversarial network(BiGAN)model with a joint discriminator structure and zero-centered gradient penalty(0-GP)is proposed.In this model,in order to improve the capability of original BiGAN in learning imbalanced parameters,the joint discriminator separately discriminates the routine activities and risk event durations to balance their influence weights.Then,the self-attention mechanism is embedded so that the discriminator can pay more attention to the imbalanced parameters.Finally,the 0-GP is adapted for the loss of the discrimi-nator to improve its convergence and stability.A case study of a tunnel in China shows that the improved BiGAN can obtain parameter estimates consistent with the classical Gauss mixture model,without the need of tedious and complex correlation analysis.The proposed joint discriminator can increase the ability of BiGAN in estimating imbalanced construction parameters,and the 0-GP can ensure the stability and convergence of the model.
