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
[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
A spacecraft attitude estimation method based on electromagnetic vector sensors(EMVS)array is proposed,which employs the orthogonally constrained parallel factor(PARAFAC)algorithm and makes use of measurements of the ...A spacecraft attitude estimation method based on electromagnetic vector sensors(EMVS)array is proposed,which employs the orthogonally constrained parallel factor(PARAFAC)algorithm and makes use of measurements of the two-dimensional direction-of-arrival(2D-DOA)and polarization angles,aiming to address the issues of incomplete,asynchronous,and inaccurate third-party reference used for attitude estimation in spacecraft docking missions by employing the electromagnetic wave’s three-dimensional(3D)wave structure as a complete third-party reference.Comparative analysis with state-ofthe-art algorithms shows significant improvements in estimation accuracy and computational efficiency with this algorithm.Numerical simulations have verified the effectiveness and superiority of this method.A high-precision,reliable,and cost-effective method for rapid spacecraft attitude estimation is provided in this paper.展开更多
The Ice,Cloud and Land Elevation Satellite-2(ICESat-2),a new spaceborne light detection and ranging(LiDAR)system,was successfully launched on September 15,2018.The ICESat-2 data increase the types of spaceborne LiDAR ...The Ice,Cloud and Land Elevation Satellite-2(ICESat-2),a new spaceborne light detection and ranging(LiDAR)system,was successfully launched on September 15,2018.The ICESat-2 data increase the types of spaceborne LiDAR data archive and provide new control point data for large-scale topographic mapping and geodetic surveying.However,the accuracy of the ATL 08 terrain estimates has not been fully evaluated on a large scale and in complex terrain conditions.This article aims to quantitatively assess the accuracy of ICESat-2 ATL 08 terrain estimates.Firstly,the ICESat-2 ATL 08 terrain estimates were compared with the high-precision airborne LiDAR digital terrain model(DTM),and impacts of acquisition time,vegetation cover type,terrain slope,and season change on the terrain estimation accuracy were analyzed.We get the following conclusions from the analysis:1)the mean and RMSE of the terrain estimates of day acquisitions are 0.22 m and 0.59 m higher than that of night acquisitions;2)the accuracy of the ATL 08 terrain estimates acquired in vegetated areas is lower than those in non-vegetated areas;3)the accuracy of the ATL 08 terrain estimates is inversely proportional to the slope,and the elevation error increases significantly when the terrain slope is larger than 30°;4)in the non-vegetation covered area,the accuracy of the ATL 08 terrain estimates of summer and winter acquisitions has no obvious discrepancy,but in vegetated area,the accuracy of winter acquisitions is significantly better than that of summer acquisitions.This research provides references for the selection and application of ICESat-2 data.展开更多
Based on the principle of statistics and the research results by Zhu Jianjun, the paper establishesthe mean Cook distance of scale parameter and studies its properties. The paper still presents the robust estimate of ...Based on the principle of statistics and the research results by Zhu Jianjun, the paper establishesthe mean Cook distance of scale parameter and studies its properties. The paper still presents the robust estimate of scale parameter with minimum mean Cook distance and theoretically shows that scale parameter isnot "nuisance parameter" and it determined by the plus weight squared sums of the residuals of observations.A simple numerical example is given.展开更多
Based on an extended Gauss-Markov model where the unknown parameters has the prior normal distribution, this paper derives the maximum posterior estimate formulas of the parameters which are proved to be unbiased,effi...Based on an extended Gauss-Markov model where the unknown parameters has the prior normal distribution, this paper derives the maximum posterior estimate formulas of the parameters which are proved to be unbiased,efficient, and of variance of unit weight which is biased. Finally, the marginal maximum posterior estimate formula of the variance with unbiased and efficient , properties is derived.展开更多
Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is pro...Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is proposed to estimate the unmeasured states and disturbance, in which the model parameters are adjusted in real time. Theoretical analysis shows that the estimation errors of the disturbances and unmeasured states converge exponentially to zero, and the parameter estimation error can be obtained from the extended state. Then, based on the extended state of the AESO, a novel parameter estimation law is designed. Due to the convergence of AESO, the novel parameter estimation law is insensitive to controllers and excitation signal. Under persistent excitation(PE) condition, the estimated parameters will converge to a compact set around the actual parameter value. Without PE signal, the estimated parameters will converge to zero for the extended state. Simulation and experimental results show that the proposed method can accurately estimate the unmeasured states and disturbance of the chain shell magazine, and the estimated parameters will converge to the actual value without strictly continuous PE signals.展开更多
The signal direction of arrival (DOA) estimate algorithm based on the eigendecomposition of the modified covariance matrix is introduced in this paper. A field test system consisting of a 4-element linear array and a ...The signal direction of arrival (DOA) estimate algorithm based on the eigendecomposition of the modified covariance matrix is introduced in this paper. A field test system consisting of a 4-element linear array and a meter band radar is also presented, which is applied to the experimental studies of the algorithms in the practical performances. The results of the test indicate that when SNR is only 5.85 dB, two airplanes being 0.25 beam width apart in azimuth can be resolved clearly.展开更多
To study the scene classification in the Synthetic Aperture Radar （SAR） image, a novel method based on kernel estimate, with the Maxkov context and Dempster-Shafer evidence theory is proposed. Initially, a nonpaxame...To study the scene classification in the Synthetic Aperture Radar （SAR） image, a novel method based on kernel estimate, with the Maxkov context and Dempster-Shafer evidence theory is proposed. Initially, a nonpaxametric Probability Density Function （PDF） estimate method is introduced, to describe the scene of SAR images. And then under the Maxkov context, both the determinate PDF and the kernel estimate method axe adopted respectively, to form a primary classification. Next, the primary classification results are fused using the evidence theory in an unsupervised way to get the scene classification. Finally, a regularization step is used, in which an iterated maximum selecting approach is introduced to control the fragments and modify the errors of the classification. Use of the kernel estimate and evidence theory can describe the complicated scenes with little prior knowledge and eliminate the ambiguities of the primary classification results. Experimental results on real SAR images illustrate a rather impressive performance.展开更多
The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean ...The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.展开更多
Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate trackin...Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.展开更多
The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncer...The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncertain dynamics.It is prone to wind disturbances that offer a challenge for a trajectory tracking control design.This paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed parameters.It uses extended Kalman filter(EKF)for uncertainty and disturbance estimation.The estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory tracking.This comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship trajectory.The proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model inaccuracies.The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis.The simulation results show that the proposed method efficiently tracks the desired trajectory.The method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.展开更多
Designing optimal time and spatial difference step size is the key technology for quantum-random filtering(QSF)to realize time-varying frequency periodic signal filtering.In this paper,it was proposed to use the short...Designing optimal time and spatial difference step size is the key technology for quantum-random filtering(QSF)to realize time-varying frequency periodic signal filtering.In this paper,it was proposed to use the short-time Fourier transform(STFT)to dynamically estimate the signal to noise ratio(SNR)and relative frequency of the input time-varying frequency periodic signal.Then the model of time and space difference step size and signal to noise ratio(SNR)and relative frequency of quantum random filter is established by least square method.Finally,the parameters of the quantum filter can be determined step by step by analyzing the characteristics of the actual signal.The simulation results of single-frequency signal and frequency time-varying signal show that the proposed method can quickly and accurately design the optimal filter parameters based on the characteristics of the input signal,and achieve significant filtering effects.展开更多
Beamspace super-resolution methods for elevation estimation in multipath environment has attracted significant attention, especially the beamspace maximum likelihood(BML)algorithm. However, the difference beam is rare...Beamspace super-resolution methods for elevation estimation in multipath environment has attracted significant attention, especially the beamspace maximum likelihood(BML)algorithm. However, the difference beam is rarely used in superresolution methods, especially in low elevation estimation. The target airspace information in the difference beam is different from the target airspace information in the sum beam. And the use of difference beams does not significantly increase the complexity of the system and algorithms. Thus, this paper applies the difference beam to the beamformer to improve the elevation estimation performance of BML algorithm. And the direction and number of beams can be adjusted according to the actual needs. The theoretical target elevation angle root means square error(RMSE) and the computational complexity of the proposed algorithms are analyzed. Finally, computer simulations and real data processing results demonstrate the effectiveness of the proposed algorithms.展开更多
The present paper deals with the problem of nonparametric kernel density estimation of the trend function for stochastic processes driven by fractional Brownian motion of the second kind.The consistency,the rate of co...The present paper deals with the problem of nonparametric kernel density estimation of the trend function for stochastic processes driven by fractional Brownian motion of the second kind.The consistency,the rate of convergence,and the asymptotic normality of the kernel-type estimator are discussed.Besides,we prove that the rate of convergence of the kernel-type estimator depends on the smoothness of the trend of the nonperturbed system.展开更多
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.
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.
文摘A spacecraft attitude estimation method based on electromagnetic vector sensors(EMVS)array is proposed,which employs the orthogonally constrained parallel factor(PARAFAC)algorithm and makes use of measurements of the two-dimensional direction-of-arrival(2D-DOA)and polarization angles,aiming to address the issues of incomplete,asynchronous,and inaccurate third-party reference used for attitude estimation in spacecraft docking missions by employing the electromagnetic wave’s three-dimensional(3D)wave structure as a complete third-party reference.Comparative analysis with state-ofthe-art algorithms shows significant improvements in estimation accuracy and computational efficiency with this algorithm.Numerical simulations have verified the effectiveness and superiority of this method.A high-precision,reliable,and cost-effective method for rapid spacecraft attitude estimation is provided in this paper.
基金Projects(41820104005,41904004,42030112)supported by the National Natural Science Foundation of China。
文摘The Ice,Cloud and Land Elevation Satellite-2(ICESat-2),a new spaceborne light detection and ranging(LiDAR)system,was successfully launched on September 15,2018.The ICESat-2 data increase the types of spaceborne LiDAR data archive and provide new control point data for large-scale topographic mapping and geodetic surveying.However,the accuracy of the ATL 08 terrain estimates has not been fully evaluated on a large scale and in complex terrain conditions.This article aims to quantitatively assess the accuracy of ICESat-2 ATL 08 terrain estimates.Firstly,the ICESat-2 ATL 08 terrain estimates were compared with the high-precision airborne LiDAR digital terrain model(DTM),and impacts of acquisition time,vegetation cover type,terrain slope,and season change on the terrain estimation accuracy were analyzed.We get the following conclusions from the analysis:1)the mean and RMSE of the terrain estimates of day acquisitions are 0.22 m and 0.59 m higher than that of night acquisitions;2)the accuracy of the ATL 08 terrain estimates acquired in vegetated areas is lower than those in non-vegetated areas;3)the accuracy of the ATL 08 terrain estimates is inversely proportional to the slope,and the elevation error increases significantly when the terrain slope is larger than 30°;4)in the non-vegetation covered area,the accuracy of the ATL 08 terrain estimates of summer and winter acquisitions has no obvious discrepancy,but in vegetated area,the accuracy of winter acquisitions is significantly better than that of summer acquisitions.This research provides references for the selection and application of ICESat-2 data.
文摘Based on the principle of statistics and the research results by Zhu Jianjun, the paper establishesthe mean Cook distance of scale parameter and studies its properties. The paper still presents the robust estimate of scale parameter with minimum mean Cook distance and theoretically shows that scale parameter isnot "nuisance parameter" and it determined by the plus weight squared sums of the residuals of observations.A simple numerical example is given.
文摘Based on an extended Gauss-Markov model where the unknown parameters has the prior normal distribution, this paper derives the maximum posterior estimate formulas of the parameters which are proved to be unbiased,efficient, and of variance of unit weight which is biased. Finally, the marginal maximum posterior estimate formula of the variance with unbiased and efficient , properties is derived.
文摘Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is proposed to estimate the unmeasured states and disturbance, in which the model parameters are adjusted in real time. Theoretical analysis shows that the estimation errors of the disturbances and unmeasured states converge exponentially to zero, and the parameter estimation error can be obtained from the extended state. Then, based on the extended state of the AESO, a novel parameter estimation law is designed. Due to the convergence of AESO, the novel parameter estimation law is insensitive to controllers and excitation signal. Under persistent excitation(PE) condition, the estimated parameters will converge to a compact set around the actual parameter value. Without PE signal, the estimated parameters will converge to zero for the extended state. Simulation and experimental results show that the proposed method can accurately estimate the unmeasured states and disturbance of the chain shell magazine, and the estimated parameters will converge to the actual value without strictly continuous PE signals.
文摘The signal direction of arrival (DOA) estimate algorithm based on the eigendecomposition of the modified covariance matrix is introduced in this paper. A field test system consisting of a 4-element linear array and a meter band radar is also presented, which is applied to the experimental studies of the algorithms in the practical performances. The results of the test indicate that when SNR is only 5.85 dB, two airplanes being 0.25 beam width apart in azimuth can be resolved clearly.
基金the National Nature Science Foundation of China (60372057).
文摘To study the scene classification in the Synthetic Aperture Radar （SAR） image, a novel method based on kernel estimate, with the Maxkov context and Dempster-Shafer evidence theory is proposed. Initially, a nonpaxametric Probability Density Function （PDF） estimate method is introduced, to describe the scene of SAR images. And then under the Maxkov context, both the determinate PDF and the kernel estimate method axe adopted respectively, to form a primary classification. Next, the primary classification results are fused using the evidence theory in an unsupervised way to get the scene classification. Finally, a regularization step is used, in which an iterated maximum selecting approach is introduced to control the fragments and modify the errors of the classification. Use of the kernel estimate and evidence theory can describe the complicated scenes with little prior knowledge and eliminate the ambiguities of the primary classification results. Experimental results on real SAR images illustrate a rather impressive performance.
文摘The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.
基金the National Natural Science Foundation of China(No.52275062)and(No.52075262).
文摘Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.
文摘The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncertain dynamics.It is prone to wind disturbances that offer a challenge for a trajectory tracking control design.This paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed parameters.It uses extended Kalman filter(EKF)for uncertainty and disturbance estimation.The estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory tracking.This comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship trajectory.The proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model inaccuracies.The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis.The simulation results show that the proposed method efficiently tracks the desired trajectory.The method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.
基金Projects(2017H0022,2016H6015)supported by Fujian Science and Technology Key Project,China
文摘Designing optimal time and spatial difference step size is the key technology for quantum-random filtering(QSF)to realize time-varying frequency periodic signal filtering.In this paper,it was proposed to use the short-time Fourier transform(STFT)to dynamically estimate the signal to noise ratio(SNR)and relative frequency of the input time-varying frequency periodic signal.Then the model of time and space difference step size and signal to noise ratio(SNR)and relative frequency of quantum random filter is established by least square method.Finally,the parameters of the quantum filter can be determined step by step by analyzing the characteristics of the actual signal.The simulation results of single-frequency signal and frequency time-varying signal show that the proposed method can quickly and accurately design the optimal filter parameters based on the characteristics of the input signal,and achieve significant filtering effects.
基金supported by the Fund for Foreign Scholars in University Research and Teaching Programs (B18039)。
文摘Beamspace super-resolution methods for elevation estimation in multipath environment has attracted significant attention, especially the beamspace maximum likelihood(BML)algorithm. However, the difference beam is rarely used in superresolution methods, especially in low elevation estimation. The target airspace information in the difference beam is different from the target airspace information in the sum beam. And the use of difference beams does not significantly increase the complexity of the system and algorithms. Thus, this paper applies the difference beam to the beamformer to improve the elevation estimation performance of BML algorithm. And the direction and number of beams can be adjusted according to the actual needs. The theoretical target elevation angle root means square error(RMSE) and the computational complexity of the proposed algorithms are analyzed. Finally, computer simulations and real data processing results demonstrate the effectiveness of the proposed algorithms.
基金Supported by the National Natural Science Foundation of China(12101004)the Natural Science Research Project of Anhui Educational Committee(2023AH030021)the Research Startup Foundation for Introducing Talent of Anhui Polytechnic University(2020YQQ064)。
文摘The present paper deals with the problem of nonparametric kernel density estimation of the trend function for stochastic processes driven by fractional Brownian motion of the second kind.The consistency,the rate of convergence,and the asymptotic normality of the kernel-type estimator are discussed.Besides,we prove that the rate of convergence of the kernel-type estimator depends on the smoothness of the trend of the nonperturbed system.
