Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as...Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as mutual coupling between array elements,array amplitude and phase errors,and array element position errors leads to defects in the array manifold,which makes the performance of the algorithm decline rapidly or even fail.In order to solve the problem of DOA estimation in the presence of amplitude and phase errors and array element position errors,this paper introduces the first-order Taylor expansion equivalent model of the received signal under the uniform linear array from the Bayesian point of view.In the solution,the amplitude and phase error parameters and the array element position error parameters are regarded as random variables obeying the Gaussian distribution.At the same time,the expectation-maximization algorithm is used to update the probability distribution parameters,and then the two error parameters are solved alternately to obtain more accurate DOA estimation results.Finally,the effectiveness of the proposed algorithm is verified by simulation and experiment.展开更多
To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a de...To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a deep unfolded amplitude-phase error self-calibration network.Firstly,a sparse-based DOA model with an array convex error restriction is established,which gets resolved via an alternating iterative minimization(AIM)algo-rithm.The algorithm is then unrolled to a deep network known as AE-AIM Network(AE-AIM-Net),where all parameters are opti-mized through multi-task learning using the constructed com-plete dataset.The results of the simulation and theoretical analy-sis suggest that the proposed unfolded network achieves lower computational costs compared to typical sparse recovery meth-ods.Furthermore,it maintains excellent estimation performance even in the presence of array magnitude-phase errors.展开更多
In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A...In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.展开更多
In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way A...In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way AF relaying mode with channel estimation error, the resultant instantaneous SNRs at end nodes is obtained. Then, by using a high SNR approximation, outage possibility is acquired and its simple closed-form expression is represented. Specially, for using the energy resource more efficiently, a low-complexity power allocation and transmission mode selection policy is proposed to enhance the energy efficiency of two-way AF relay system. Finally, relay priority region is identified in which cooperative diversity energy gain can be achieved. The computer simulations are presented to verify our analytical results, indicating that the proposed policy outperforms direct transmission by an energy gain of 3 dB at the relative channel estimation error less than 0.001. The results also show that the two-way AF relaying transmission loses the two-way AF relaying transmission loses its superiority to direct transmission in terms of energy efficiency when channel estimation error reaches 0.03.展开更多
Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matri...Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.展开更多
For multi-channel synthetic aperture radar（SAR） systems, since the minimum antenna area constraint is eliminated,wide swath and high resolution SAR image can be achieved.However, the unavoidable array errors, consis...For multi-channel synthetic aperture radar（SAR） systems, since the minimum antenna area constraint is eliminated,wide swath and high resolution SAR image can be achieved.However, the unavoidable array errors, consisting of channel gainphase mismatch and position uncertainty, significantly degrade the performance of such systems. An iteration-free method is proposed to simultaneously estimate position and gain-phase errors.In our research, the steering vectors corresponding to a pair of Doppler bins within the same range bin are studied in terms of their rotational relationships. The method is based on the fact that the rotational matrix only depends on the position errors and the frequency spacing between the paired Doppler bins but is independent of gain-phase error. Upon combining the projection matrices corresponding to the paired Doppler bins, the position errors are directly obtained in terms of extracting the rotational matrix in a least squares framework. The proposed method, when used in conjunction with the self-calibration algorithm, performs stably as well as has less computational load, compared with the conventional methods. Simulations reveal that the proposed method behaves better than the conventional methods even when the signal-to-noise ratio（SNR） is low.展开更多
The presence of array imperfection and mutual coupling in sensor arrays poses several challenges for development of effective algorithms for the direction-of-arrival （DOA） estimation problem in array processing. A c...The presence of array imperfection and mutual coupling in sensor arrays poses several challenges for development of effective algorithms for the direction-of-arrival （DOA） estimation problem in array processing. A correlation domain wideband DOA estimation algorithm without array calibration is proposed, to deal with these array model errors, using the arbitrary antenna array of omnidirectional elements. By using the matrix operators that have the memory and oblivion characteristics, this algorithm can separate the incident signals effectively. Compared with other typical wideband DOA estimation algorithms based on the subspace theory, this algorithm can get robust DOA estimation with regard to position error, gain-phase error, and mutual coupling, by utilizing a relaxation technique based on signal separation. The signal separation category and the robustness of this algorithm to the array model errors are analyzed and proved. The validity and robustness of this algorithm, in the presence of array model errors, are confirmed by theoretical analysis and simulation results.展开更多
Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation...Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.展开更多
Most of the direction of arrival(DOA) estimation methods often need the exact array manifold, but in actual applications,the gain and phase of the channels are usually inconsistent, which will cause the estimation inv...Most of the direction of arrival(DOA) estimation methods often need the exact array manifold, but in actual applications,the gain and phase of the channels are usually inconsistent, which will cause the estimation invalid. A novel direction finding approach for mixed far-field and near-field signals with gain-phase error array is provided. Based on simplifying the space spectrum function by matrix transformation, DOA of far-field signals is obtained. Consequently, errors of the array are acquired according to the orthogonality of far-field signal subspace and noise subspace.Finally, DOA of near-field signals can be estimated. The method merely needs one-dimensional spectrum searching, so as to improve the computational efficiency on the premise of ensuring a certain accuracy, simulation results manifest the effectiveness of the method.展开更多
The error coefficient estimation of inertial platform in the course of its consecutive ground calibration is studied.A separate-bias algorithm is adopted to estimate the error parameters effectively. The ill-condition...The error coefficient estimation of inertial platform in the course of its consecutive ground calibration is studied.A separate-bias algorithm is adopted to estimate the error parameters effectively. The ill-conditioning problem of the equation solution caused by the huge state dimension is also resolved. And the simulation result shows its validity.展开更多
Traditionally, it is widely accepted that measurement error usually obeys the normal distribution. However, in this paper a new idea is proposed that the error in digitized data which is a major derived data source in...Traditionally, it is widely accepted that measurement error usually obeys the normal distribution. However, in this paper a new idea is proposed that the error in digitized data which is a major derived data source in GIS does not obey the normal distribution but the p-norm distribution with a determinate parameter. Assuming that the error is random and has the same statistical properties, the probability density function of the normal distribution, Laplace distribution and p-norm distribution are derived based on the arithmetic mean axiom, median axiom and p-median axiom, which means that the normal distribution is only one of these distributions but not the least one. Based on this ideal distribution fitness tests such as Skewness and Kurtosis coefficient test, Pearson chi-square chi(2) test and Kolmogorov test for digitized data are conducted. The results show that the error in map digitization obeys the p-norm distribution whose parameter is close to 1.60. A least p-norm estimation and the least square estimation of digitized data are further analyzed, showing that the least p-norm adjustment is better than the least square adjustment for digitized data processing in GIS.展开更多
In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads th...In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads the electromagnetic bandgap structure on the upper surface of the substrate integrated waveguide.This is equivalent to including an additional inductance-capacitance for energy storage,which realizes the slow-wave effect.A microstrip line-SIW tapered transition structure is introduced to achieve a low loss and a large bandwidth.In the frequency band between 8-12 GHz,the measured results show that the delay multiplier of the delay line reaches 4 times,i.e.,delay line’s delay time is 4 times larger than 50Ωmicrostrip line with same length.Furthermore,the delay fluctuation,i.e.,the difference between the maximum and minimum delay as a percentage of the standard delay is only 2.5%,the insertion loss is less than-2.5 dB,and the return loss is less than-15 dB.Compared with the existing delay lines,the proposed delay line has the advantages of high delay efficiency,low delay error,wide bandwidth and low loss,which has good practical value and application prospects.展开更多
In this paper,we develop a multi-scalar auxiliary variables(MSAV)scheme for the Cahn-Hilliard Magnetohydrodynamics system by introducing two scalar auxiliary variables(SAV).This scheme is linear,fully decoupled and un...In this paper,we develop a multi-scalar auxiliary variables(MSAV)scheme for the Cahn-Hilliard Magnetohydrodynamics system by introducing two scalar auxiliary variables(SAV).This scheme is linear,fully decoupled and unconditionally stable in energy.Subsequently,we provide a detailed implementation procedure for full decoupling.Thus,at each time step,only a series of linear differential equations with constant coefficients need to be solved.To validate the effectiveness of our approach,we conduct an error analysis for this first-order scheme.Finally,some numerical experiments are provided to verify the energy dissipation of the system and the convergence of the proposed approach.展开更多
An improved estimation of distribution algorithm(IEDA)is proposed in this paper for efficient design of metamaterial absorbers.This algorithm establishes a probability model through the selected dominant groups and sa...An improved estimation of distribution algorithm(IEDA)is proposed in this paper for efficient design of metamaterial absorbers.This algorithm establishes a probability model through the selected dominant groups and samples from the model to obtain the next generation,avoiding the problem of building-blocks destruction caused by crossover and mutation.Neighboring search from artificial bee colony algorithm(ABCA)is introduced to enhance the local optimization ability and improved to raise the speed of convergence.The probability model is modified by boundary correction and loss correction to enhance the robustness of the algorithm.The proposed IEDA is compared with other intelligent algorithms in relevant references.The results show that the proposed IEDA has faster convergence speed and stronger optimization ability,proving the feasibility and effectiveness of the algorithm.展开更多
Accurate target angle estimation is one of the chal-lenges for wideband radars due to the fact that target occupies multiple range bins,resulting in lower energy or signal to noise ratio in a single range bin.This pap...Accurate target angle estimation is one of the chal-lenges for wideband radars due to the fact that target occupies multiple range bins,resulting in lower energy or signal to noise ratio in a single range bin.This paper proposes a processing technique for enhanced accuracy of target angle estimates for wideband monopulse radars.Firstly,to accumulate the energy of the received echo signals from different scatterers on a target,the phase difference between different scatterers on a target is estimated using the minimum entropy phase estimation method combining with the correlation between adjacent pulses.Then,the monopulse ratio is obtained by using the signals from the accumulated sum and difference channels.The target angle is estimated by weighting the accumulated echo energy for accu-racy enhancement.Experimental results based on both numeri-cal simulation and measured data are presented to validate the effectiveness of the proposed technique.展开更多
Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has seve...Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has severely restricted the applications of high-precision FOGs.The conventional methods for suppressing vibration-induced errors mostly concentrate on reinforcing the mechanical structure and optical path as well as the compensation under some specific operation parameters,which have very limited effects for high-precision FOGs maintaining performances under vibration.In this work,a technique of suppressing the vibration-induced bias deviation through removing the part related to the varying gain from the rotation-rate output is put forward.Particularly,the loop gain is extracted out by adding a gain-monitoring wave.By demodulating the loop gain and the rotation rate simultaneously under distinct frequencies and investigating their quantitative relationship,the vibrationinduced bias error is compensated without limiting the operating parameters or environments,like the applied modulation depth.The experimental results show that the proposed method has achieved the reduction of bias error from about 0.149°/h to0.014°/h during the random vibration with frequencies from20 Hz to 2000 Hz.This technique provides a feasible route for enhancing the performances of high-precision FOGs heading towards high environmental adaptability.展开更多
[Objective]Fish pose estimation(FPE)provides fish physiological information,facilitating health monitoring in aquaculture.It aids decision-making in areas such as fish behavior recognition.When fish are injured or def...[Objective]Fish pose estimation(FPE)provides fish physiological information,facilitating health monitoring in aquaculture.It aids decision-making in areas such as fish behavior recognition.When fish are injured or deficient,they often display abnormal behaviors and noticeable changes in the positioning of their body parts.Moreover,the unpredictable posture and orientation of fish during swimming,combined with the rapid swimming speed of fish,restrict the current scope of research in FPE.In this research,a FPE model named HPFPE is presented to capture the swimming posture of fish and accurately detect their key points.[Methods]On the one hand,this model incorporated the CBAM module into the HRNet framework.The attention module enhanced accuracy without adding computational complexity,while effectively capturing a broader range of contextual information.On the other hand,the model incorporated dilated convolution to increase the receptive field,allowing it to capture more spatial context.[Results and Discussions]Experiments showed that compared with the baseline method,the average precision(AP)of HPFPE based on different backbones and input sizes on the oplegnathus punctatus datasets had increased by 0.62,1.35,1.76,and 1.28 percent point,respectively,while the average recall(AR)had also increased by 0.85,1.50,1.40,and 1.00,respectively.Additionally,HPFPE outperformed other mainstream methods,including DeepPose,CPM,SCNet,and Lite-HRNet.Furthermore,when compared to other methods using the ornamental fish data,HPFPE achieved the highest AP and AR values of 52.96%,and 59.50%,respectively.[Conclusions]The proposed HPFPE can accurately estimate fish posture and assess their swimming patterns,serving as a valuable reference for applications such as fish behavior recognition.展开更多
For target tracking and localization in bearing-only sensor network,it is an essential and significant challenge to solve the problem of plug-and-play expansion while stably enhancing the accuracy of state estimation....For target tracking and localization in bearing-only sensor network,it is an essential and significant challenge to solve the problem of plug-and-play expansion while stably enhancing the accuracy of state estimation.This paper pro-poses a distributed state estimation method based on two-layer factor graph.Firstly,the measurement model of the bearing-only sensor network is constructed,and by investigating the observ-ability and the Cramer-Rao lower bound of the system model,the preconditions are analyzed.Subsequently,the location fac-tor graph and cubature information filtering algorithm of sensor node pairs are proposed for localized estimation.Building upon this foundation,the mechanism for propagating confidence mes-sages within the fusion factor graph is designed,and is extended to the entire sensor network to achieve global state estimation.Finally,groups of simulation experiments are con-ducted to compare and analyze the results,which verifies the rationality,effectiveness,and superiority of the proposed method.展开更多
Gear assembly errors can lead to the increase of vibration and noise of the system,which affect the stability of system.The influence can be compensated by tooth modification.Firstly,an improved three-dimensional load...Gear assembly errors can lead to the increase of vibration and noise of the system,which affect the stability of system.The influence can be compensated by tooth modification.Firstly,an improved three-dimensional loaded tooth contact analysis(3D-LTCA)method which can consider tooth modification and coupling assembly errors is proposed,and mesh stiffness calculated by proposed method is verified by MASTA software.Secondly,based on neural network,the surrogate model(SM)that maps the relationship between modification parameters and mesh mechanical parameters is established,and its accuracy is verified.Finally,SM is introduced to establish an optimization model with the target of minimizing mesh stiffness variations and obtaining more even load distribution on mesh surface.The results show that even considering training time,the efficiency of gear pair optimization by surrogate model is still much higher than that by LTCA method.After optimization,the mesh stiffness fluctuation of gear pair with coupling assembly error is reduced by 34.10%,and difference in average contact stresses between left and right regions of the mesh surface is reduced by 62.84%.展开更多
As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely...As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely used in aerospace, unmanned driving, and other fields. However, due to the temper-ature sensitivity of optical devices, the influence of environmen-tal temperature causes errors in FOG, thereby greatly limiting their output accuracy. This work researches on machine-learn-ing based temperature error compensation techniques for FOG. Specifically, it focuses on compensating for the bias errors gen-erated in the fiber ring due to the Shupe effect. This work pro-poses a composite model based on k-means clustering, sup-port vector regression, and particle swarm optimization algo-rithms. And it significantly reduced redundancy within the sam-ples by adopting the interval sequence sample. Moreover, met-rics such as root mean square error (RMSE), mean absolute error (MAE), bias stability, and Allan variance, are selected to evaluate the model’s performance and compensation effective-ness. This work effectively enhances the consistency between data and models across different temperature ranges and tem-perature gradients, improving the bias stability of the FOG from 0.022 °/h to 0.006 °/h. Compared to the existing methods utiliz-ing a single machine learning model, the proposed method increases the bias stability of the compensated FOG from 57.11% to 71.98%, and enhances the suppression of rate ramp noise coefficient from 2.29% to 14.83%. This work improves the accuracy of FOG after compensation, providing theoretical guid-ance and technical references for sensors error compensation work in other fields.展开更多
基金supported by the National Natural Science Foundation of China (62071144)
文摘Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as mutual coupling between array elements,array amplitude and phase errors,and array element position errors leads to defects in the array manifold,which makes the performance of the algorithm decline rapidly or even fail.In order to solve the problem of DOA estimation in the presence of amplitude and phase errors and array element position errors,this paper introduces the first-order Taylor expansion equivalent model of the received signal under the uniform linear array from the Bayesian point of view.In the solution,the amplitude and phase error parameters and the array element position error parameters are regarded as random variables obeying the Gaussian distribution.At the same time,the expectation-maximization algorithm is used to update the probability distribution parameters,and then the two error parameters are solved alternately to obtain more accurate DOA estimation results.Finally,the effectiveness of the proposed algorithm is verified by simulation and experiment.
基金supported by the National Natural Science Foundation of China(62301598).
文摘To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a deep unfolded amplitude-phase error self-calibration network.Firstly,a sparse-based DOA model with an array convex error restriction is established,which gets resolved via an alternating iterative minimization(AIM)algo-rithm.The algorithm is then unrolled to a deep network known as AE-AIM Network(AE-AIM-Net),where all parameters are opti-mized through multi-task learning using the constructed com-plete dataset.The results of the simulation and theoretical analy-sis suggest that the proposed unfolded network achieves lower computational costs compared to typical sparse recovery meth-ods.Furthermore,it maintains excellent estimation performance even in the presence of array magnitude-phase errors.
基金supported by the National Natural Science Foundation of China(91538201)
文摘In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.
基金Project(IRT0852) supported by the Program for Changjiang Scholars and Innovative Research Team in University,ChinaProject(2012CB316100) supported by the National Basic Research Program of China+2 种基金Projects(61101144,61101145) supported by the National Natural Science Foundation of ChinaProject(B08038) supported by the "111" Project,ChinaProject(K50510010017) supported by the Fundamental Research Funds for the Central Universities,China
文摘In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way AF relaying mode with channel estimation error, the resultant instantaneous SNRs at end nodes is obtained. Then, by using a high SNR approximation, outage possibility is acquired and its simple closed-form expression is represented. Specially, for using the energy resource more efficiently, a low-complexity power allocation and transmission mode selection policy is proposed to enhance the energy efficiency of two-way AF relay system. Finally, relay priority region is identified in which cooperative diversity energy gain can be achieved. The computer simulations are presented to verify our analytical results, indicating that the proposed policy outperforms direct transmission by an energy gain of 3 dB at the relative channel estimation error less than 0.001. The results also show that the two-way AF relaying transmission loses the two-way AF relaying transmission loses its superiority to direct transmission in terms of energy efficiency when channel estimation error reaches 0.03.
基金This work is supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX18_0467)Jiangsu Province,China.During the revision of this paper,the author is supported by China Scholarship Council(No.201906840021)China to continue some research related to data processing.
文摘Kalman filter is commonly used in data filtering and parameters estimation of nonlinear system,such as projectile's trajectory estimation and control.While there is a drawback that the prior error covariance matrix and filter parameters are difficult to be determined,which may result in filtering divergence.As to the problem that the accuracy of state estimation for nonlinear ballistic model strongly depends on its mathematical model,we improve the weighted least squares method(WLSM)with minimum model error principle.Invariant embedding method is adopted to solve the cost function including the model error.With the knowledge of measurement data and measurement error covariance matrix,we use gradient descent algorithm to determine the weighting matrix of model error.The uncertainty and linearization error of model are recursively estimated by the proposed method,thus achieving an online filtering estimation of the observations.Simulation results indicate that the proposed recursive estimation algorithm is insensitive to initial conditions and of good robustness.
基金supported by the Natural Science Basic Research Plan in Shaanxi Province of China(2015JM6278)the China Postdoctoral Science Foundation(2015M582586)the China Academy of Space Technology Innovation Fund
文摘For multi-channel synthetic aperture radar（SAR） systems, since the minimum antenna area constraint is eliminated,wide swath and high resolution SAR image can be achieved.However, the unavoidable array errors, consisting of channel gainphase mismatch and position uncertainty, significantly degrade the performance of such systems. An iteration-free method is proposed to simultaneously estimate position and gain-phase errors.In our research, the steering vectors corresponding to a pair of Doppler bins within the same range bin are studied in terms of their rotational relationships. The method is based on the fact that the rotational matrix only depends on the position errors and the frequency spacing between the paired Doppler bins but is independent of gain-phase error. Upon combining the projection matrices corresponding to the paired Doppler bins, the position errors are directly obtained in terms of extracting the rotational matrix in a least squares framework. The proposed method, when used in conjunction with the self-calibration algorithm, performs stably as well as has less computational load, compared with the conventional methods. Simulations reveal that the proposed method behaves better than the conventional methods even when the signal-to-noise ratio（SNR） is low.
基金supported by the National "863" High Technology Research and Development Program of China(2007AA703428)
文摘The presence of array imperfection and mutual coupling in sensor arrays poses several challenges for development of effective algorithms for the direction-of-arrival （DOA） estimation problem in array processing. A correlation domain wideband DOA estimation algorithm without array calibration is proposed, to deal with these array model errors, using the arbitrary antenna array of omnidirectional elements. By using the matrix operators that have the memory and oblivion characteristics, this algorithm can separate the incident signals effectively. Compared with other typical wideband DOA estimation algorithms based on the subspace theory, this algorithm can get robust DOA estimation with regard to position error, gain-phase error, and mutual coupling, by utilizing a relaxation technique based on signal separation. The signal separation category and the robustness of this algorithm to the array model errors are analyzed and proved. The validity and robustness of this algorithm, in the presence of array model errors, are confirmed by theoretical analysis and simulation results.
基金supported by the State Key Laboratory of Geo-Information Engineering(SKLGIE2022-Z-2-1)the National Natural Science Foundation of China(41674024,42174036).
文摘Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.
基金supported by the National Natural Science Foundation of China(6150117661505050)+5 种基金the University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province(UNPYSCT-2016017)the Natural Science Foundation of Heilongjiang Province(F2015015)the Outstanding Young Scientist Foundation of Heilongjiang University(JCL201504)the China Postdoctoral Science Foundation(2014M561381)the Postdoctoral Foundation of Heilongjiang Province(LBH-Z14178)the Special Research Funds for the Universities of Heilongjiang Province(HDRCCX-2016Z10)
文摘Most of the direction of arrival(DOA) estimation methods often need the exact array manifold, but in actual applications,the gain and phase of the channels are usually inconsistent, which will cause the estimation invalid. A novel direction finding approach for mixed far-field and near-field signals with gain-phase error array is provided. Based on simplifying the space spectrum function by matrix transformation, DOA of far-field signals is obtained. Consequently, errors of the array are acquired according to the orthogonality of far-field signal subspace and noise subspace.Finally, DOA of near-field signals can be estimated. The method merely needs one-dimensional spectrum searching, so as to improve the computational efficiency on the premise of ensuring a certain accuracy, simulation results manifest the effectiveness of the method.
文摘The error coefficient estimation of inertial platform in the course of its consecutive ground calibration is studied.A separate-bias algorithm is adopted to estimate the error parameters effectively. The ill-conditioning problem of the equation solution caused by the huge state dimension is also resolved. And the simulation result shows its validity.
文摘Traditionally, it is widely accepted that measurement error usually obeys the normal distribution. However, in this paper a new idea is proposed that the error in digitized data which is a major derived data source in GIS does not obey the normal distribution but the p-norm distribution with a determinate parameter. Assuming that the error is random and has the same statistical properties, the probability density function of the normal distribution, Laplace distribution and p-norm distribution are derived based on the arithmetic mean axiom, median axiom and p-median axiom, which means that the normal distribution is only one of these distributions but not the least one. Based on this ideal distribution fitness tests such as Skewness and Kurtosis coefficient test, Pearson chi-square chi(2) test and Kolmogorov test for digitized data are conducted. The results show that the error in map digitization obeys the p-norm distribution whose parameter is close to 1.60. A least p-norm estimation and the least square estimation of digitized data are further analyzed, showing that the least p-norm adjustment is better than the least square adjustment for digitized data processing in GIS.
基金Supported by the National Natural Science Foundation of China(61971401)。
文摘In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads the electromagnetic bandgap structure on the upper surface of the substrate integrated waveguide.This is equivalent to including an additional inductance-capacitance for energy storage,which realizes the slow-wave effect.A microstrip line-SIW tapered transition structure is introduced to achieve a low loss and a large bandwidth.In the frequency band between 8-12 GHz,the measured results show that the delay multiplier of the delay line reaches 4 times,i.e.,delay line’s delay time is 4 times larger than 50Ωmicrostrip line with same length.Furthermore,the delay fluctuation,i.e.,the difference between the maximum and minimum delay as a percentage of the standard delay is only 2.5%,the insertion loss is less than-2.5 dB,and the return loss is less than-15 dB.Compared with the existing delay lines,the proposed delay line has the advantages of high delay efficiency,low delay error,wide bandwidth and low loss,which has good practical value and application prospects.
基金Research Project Supported by Shanxi Scholarship Council of China(2021-029)International Cooperation Base and Platform Project of Shanxi Province(202104041101019)Basic Research Plan of Shanxi Province(202203021211129)。
文摘In this paper,we develop a multi-scalar auxiliary variables(MSAV)scheme for the Cahn-Hilliard Magnetohydrodynamics system by introducing two scalar auxiliary variables(SAV).This scheme is linear,fully decoupled and unconditionally stable in energy.Subsequently,we provide a detailed implementation procedure for full decoupling.Thus,at each time step,only a series of linear differential equations with constant coefficients need to be solved.To validate the effectiveness of our approach,we conduct an error analysis for this first-order scheme.Finally,some numerical experiments are provided to verify the energy dissipation of the system and the convergence of the proposed approach.
基金supported by the National Key Research and Development Program(2021YFB3502500).
文摘An improved estimation of distribution algorithm(IEDA)is proposed in this paper for efficient design of metamaterial absorbers.This algorithm establishes a probability model through the selected dominant groups and samples from the model to obtain the next generation,avoiding the problem of building-blocks destruction caused by crossover and mutation.Neighboring search from artificial bee colony algorithm(ABCA)is introduced to enhance the local optimization ability and improved to raise the speed of convergence.The probability model is modified by boundary correction and loss correction to enhance the robustness of the algorithm.The proposed IEDA is compared with other intelligent algorithms in relevant references.The results show that the proposed IEDA has faster convergence speed and stronger optimization ability,proving the feasibility and effectiveness of the algorithm.
文摘Accurate target angle estimation is one of the chal-lenges for wideband radars due to the fact that target occupies multiple range bins,resulting in lower energy or signal to noise ratio in a single range bin.This paper proposes a processing technique for enhanced accuracy of target angle estimates for wideband monopulse radars.Firstly,to accumulate the energy of the received echo signals from different scatterers on a target,the phase difference between different scatterers on a target is estimated using the minimum entropy phase estimation method combining with the correlation between adjacent pulses.Then,the monopulse ratio is obtained by using the signals from the accumulated sum and difference channels.The target angle is estimated by weighting the accumulated echo energy for accu-racy enhancement.Experimental results based on both numeri-cal simulation and measured data are presented to validate the effectiveness of the proposed technique.
基金Fundamental Research Funds for the Central Universities(YWF-23-L-1225)National Natural Science Foundation of China(62201025)Chinese Aeronautical Establishment(2022Z037051001)。
文摘Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has severely restricted the applications of high-precision FOGs.The conventional methods for suppressing vibration-induced errors mostly concentrate on reinforcing the mechanical structure and optical path as well as the compensation under some specific operation parameters,which have very limited effects for high-precision FOGs maintaining performances under vibration.In this work,a technique of suppressing the vibration-induced bias deviation through removing the part related to the varying gain from the rotation-rate output is put forward.Particularly,the loop gain is extracted out by adding a gain-monitoring wave.By demodulating the loop gain and the rotation rate simultaneously under distinct frequencies and investigating their quantitative relationship,the vibrationinduced bias error is compensated without limiting the operating parameters or environments,like the applied modulation depth.The experimental results show that the proposed method has achieved the reduction of bias error from about 0.149°/h to0.014°/h during the random vibration with frequencies from20 Hz to 2000 Hz.This technique provides a feasible route for enhancing the performances of high-precision FOGs heading towards high environmental adaptability.
文摘[Objective]Fish pose estimation(FPE)provides fish physiological information,facilitating health monitoring in aquaculture.It aids decision-making in areas such as fish behavior recognition.When fish are injured or deficient,they often display abnormal behaviors and noticeable changes in the positioning of their body parts.Moreover,the unpredictable posture and orientation of fish during swimming,combined with the rapid swimming speed of fish,restrict the current scope of research in FPE.In this research,a FPE model named HPFPE is presented to capture the swimming posture of fish and accurately detect their key points.[Methods]On the one hand,this model incorporated the CBAM module into the HRNet framework.The attention module enhanced accuracy without adding computational complexity,while effectively capturing a broader range of contextual information.On the other hand,the model incorporated dilated convolution to increase the receptive field,allowing it to capture more spatial context.[Results and Discussions]Experiments showed that compared with the baseline method,the average precision(AP)of HPFPE based on different backbones and input sizes on the oplegnathus punctatus datasets had increased by 0.62,1.35,1.76,and 1.28 percent point,respectively,while the average recall(AR)had also increased by 0.85,1.50,1.40,and 1.00,respectively.Additionally,HPFPE outperformed other mainstream methods,including DeepPose,CPM,SCNet,and Lite-HRNet.Furthermore,when compared to other methods using the ornamental fish data,HPFPE achieved the highest AP and AR values of 52.96%,and 59.50%,respectively.[Conclusions]The proposed HPFPE can accurately estimate fish posture and assess their swimming patterns,serving as a valuable reference for applications such as fish behavior recognition.
基金supported by the National Natural Science Foundation of China(62176214).
文摘For target tracking and localization in bearing-only sensor network,it is an essential and significant challenge to solve the problem of plug-and-play expansion while stably enhancing the accuracy of state estimation.This paper pro-poses a distributed state estimation method based on two-layer factor graph.Firstly,the measurement model of the bearing-only sensor network is constructed,and by investigating the observ-ability and the Cramer-Rao lower bound of the system model,the preconditions are analyzed.Subsequently,the location fac-tor graph and cubature information filtering algorithm of sensor node pairs are proposed for localized estimation.Building upon this foundation,the mechanism for propagating confidence mes-sages within the fusion factor graph is designed,and is extended to the entire sensor network to achieve global state estimation.Finally,groups of simulation experiments are con-ducted to compare and analyze the results,which verifies the rationality,effectiveness,and superiority of the proposed method.
基金Project(11972112)supported by the National Natural Science Foundation of ChinaProject(N2103024)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(J2019-IV-0018-0086)supported by the National Science and Technology Major Project,China。
文摘Gear assembly errors can lead to the increase of vibration and noise of the system,which affect the stability of system.The influence can be compensated by tooth modification.Firstly,an improved three-dimensional loaded tooth contact analysis(3D-LTCA)method which can consider tooth modification and coupling assembly errors is proposed,and mesh stiffness calculated by proposed method is verified by MASTA software.Secondly,based on neural network,the surrogate model(SM)that maps the relationship between modification parameters and mesh mechanical parameters is established,and its accuracy is verified.Finally,SM is introduced to establish an optimization model with the target of minimizing mesh stiffness variations and obtaining more even load distribution on mesh surface.The results show that even considering training time,the efficiency of gear pair optimization by surrogate model is still much higher than that by LTCA method.After optimization,the mesh stiffness fluctuation of gear pair with coupling assembly error is reduced by 34.10%,and difference in average contact stresses between left and right regions of the mesh surface is reduced by 62.84%.
基金supported by the National Natural Science Foundation of China(62375013).
文摘As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely used in aerospace, unmanned driving, and other fields. However, due to the temper-ature sensitivity of optical devices, the influence of environmen-tal temperature causes errors in FOG, thereby greatly limiting their output accuracy. This work researches on machine-learn-ing based temperature error compensation techniques for FOG. Specifically, it focuses on compensating for the bias errors gen-erated in the fiber ring due to the Shupe effect. This work pro-poses a composite model based on k-means clustering, sup-port vector regression, and particle swarm optimization algo-rithms. And it significantly reduced redundancy within the sam-ples by adopting the interval sequence sample. Moreover, met-rics such as root mean square error (RMSE), mean absolute error (MAE), bias stability, and Allan variance, are selected to evaluate the model’s performance and compensation effective-ness. This work effectively enhances the consistency between data and models across different temperature ranges and tem-perature gradients, improving the bias stability of the FOG from 0.022 °/h to 0.006 °/h. Compared to the existing methods utiliz-ing a single machine learning model, the proposed method increases the bias stability of the compensated FOG from 57.11% to 71.98%, and enhances the suppression of rate ramp noise coefficient from 2.29% to 14.83%. This work improves the accuracy of FOG after compensation, providing theoretical guid-ance and technical references for sensors error compensation work in other fields.
