Object tracking with abrupt motion is an important research topic and has attracted wide attention.To obtain accurate tracking results,an improved particle filter tracking algorithm based on sparse representation and ...Object tracking with abrupt motion is an important research topic and has attracted wide attention.To obtain accurate tracking results,an improved particle filter tracking algorithm based on sparse representation and nonlinear resampling is proposed in this paper. First,the sparse representation is used to compute particle weights by considering the fact that the weights are sparse when the object moves abruptly,so the potential object region can be predicted more precisely. Then,a nonlinear resampling process is proposed by utilizing the nonlinear sorting strategy,which can solve the problem of particle diversity impoverishment caused by traditional resampling methods. Experimental results based on videos containing objects with various abrupt motions have demonstrated the effectiveness of the proposed algorithm.展开更多
Land data assimilation(DA) has gradually developed into an important earth science research method because of its ability to combine model simulations and observations.Integrating new observations into a land surface ...Land data assimilation(DA) has gradually developed into an important earth science research method because of its ability to combine model simulations and observations.Integrating new observations into a land surface model by the DA method can correct the predicted trajectory of the model and thus,improve the accuracy of state variables.It can also reduce uncertainties in the model by estimating some model parameters simultaneously.Among the various DA methods,the particle filter is free from the constraints of linear models and Gaussian error distributions,and can be applicable to any nonlinear and non-Gaussian state-space model;therefore,its importance in land data assimilation research has increased.In this study,a DA scheme was developed based on the residual resampling particle filter.Microwave brightness temperatures were assimilated into the macro-scale semi-distributed variance infiltration capacity model to estimate the surface soil moisture and three hydraulic parameters simultaneously.Finally,to verify the scheme,a series of comparative experiments was performed with experimental data obtained during the Soil Moisture Experiment of 2004 in Arizona.The results show that the scheme can improve the accuracy of soil moisture estimations significantly.In addition,the three hydraulic parameters were also well estimated,demonstrating the effectiveness of the DA scheme.展开更多
In the mechanical fault detection and diagnosis field, it is more and more important to analyze the instantaneous frequency （IF） character of complex vibration signal. The improved IF estimation method is put forwar...In the mechanical fault detection and diagnosis field, it is more and more important to analyze the instantaneous frequency （IF） character of complex vibration signal. The improved IF estimation method is put forward aiming at the shortage of traditional Hilbert transform. It is based on Hilbert transform in wavelet domain. With the help of relationship between the real part and the imaginary part obtained from the complex coefficient of continuous wavelet transform or the analyti- cal signal reconstructed in wavelet packet decomposition, the instantaneous phase function of the subcomponent is extracted. In order to improve the precise of IF estimated out, some means such as Linear regression, adaptive filtering, resampling are applied into the instantaneous phase obtained, then, the central differencing operator is used to get desired IF. Simulation results with synthetic and gearbox fault signals are included to illustrate the proposed method.展开更多
基金Supported by the National Natural Science Foundation of China(61701029)
文摘Object tracking with abrupt motion is an important research topic and has attracted wide attention.To obtain accurate tracking results,an improved particle filter tracking algorithm based on sparse representation and nonlinear resampling is proposed in this paper. First,the sparse representation is used to compute particle weights by considering the fact that the weights are sparse when the object moves abruptly,so the potential object region can be predicted more precisely. Then,a nonlinear resampling process is proposed by utilizing the nonlinear sorting strategy,which can solve the problem of particle diversity impoverishment caused by traditional resampling methods. Experimental results based on videos containing objects with various abrupt motions have demonstrated the effectiveness of the proposed algorithm.
基金supported by the Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences under the project "High-resolution Optical Image Automatic Target Recognition"(Grant No.Y2YY02101B)
文摘Land data assimilation(DA) has gradually developed into an important earth science research method because of its ability to combine model simulations and observations.Integrating new observations into a land surface model by the DA method can correct the predicted trajectory of the model and thus,improve the accuracy of state variables.It can also reduce uncertainties in the model by estimating some model parameters simultaneously.Among the various DA methods,the particle filter is free from the constraints of linear models and Gaussian error distributions,and can be applicable to any nonlinear and non-Gaussian state-space model;therefore,its importance in land data assimilation research has increased.In this study,a DA scheme was developed based on the residual resampling particle filter.Microwave brightness temperatures were assimilated into the macro-scale semi-distributed variance infiltration capacity model to estimate the surface soil moisture and three hydraulic parameters simultaneously.Finally,to verify the scheme,a series of comparative experiments was performed with experimental data obtained during the Soil Moisture Experiment of 2004 in Arizona.The results show that the scheme can improve the accuracy of soil moisture estimations significantly.In addition,the three hydraulic parameters were also well estimated,demonstrating the effectiveness of the DA scheme.
基金This project is supported by National Natural Science Foundation of China (No.50605065)Natural Science Foundation Project of CQ CSTC(No.2007BB2142).
文摘In the mechanical fault detection and diagnosis field, it is more and more important to analyze the instantaneous frequency （IF） character of complex vibration signal. The improved IF estimation method is put forward aiming at the shortage of traditional Hilbert transform. It is based on Hilbert transform in wavelet domain. With the help of relationship between the real part and the imaginary part obtained from the complex coefficient of continuous wavelet transform or the analyti- cal signal reconstructed in wavelet packet decomposition, the instantaneous phase function of the subcomponent is extracted. In order to improve the precise of IF estimated out, some means such as Linear regression, adaptive filtering, resampling are applied into the instantaneous phase obtained, then, the central differencing operator is used to get desired IF. Simulation results with synthetic and gearbox fault signals are included to illustrate the proposed method.
