Based on the idea of zeroing the line of sight rate（LOSR）,a novel nonlinear differential geometric（DG） law for intercepting the agile target is proposed.In the first part,the DG formulations are utilized to descri...Based on the idea of zeroing the line of sight rate（LOSR）,a novel nonlinear differential geometric（DG） law for intercepting the agile target is proposed.In the first part,the DG formulations are utilized to describe the relatively kinematics model of missile and target,and the nonlinear DG guidance（DGG） law is proposed based on the nonlinear control theory to eliminate the influence brought by target.Further,the missile guidance commands are derived to overcome the information loss caused by decoupling condition,the new necessary initial condition is developed to guarantee capture the agile target.Then,the designed nonlinear DGG commands are transformed from an arc-length system to the time domain.A desirable aspect of the designed guidance law is that it does not require rigorous information about target acceleration.Representative numerical results show that the designed guidance law obtain a better performance than the traditional DGG law for agile target.展开更多
A parallel nonlinear energy sink(NES) is proposed and analyzed. The parallel NES is composed of a vibro-impact(VI) NES and a cubic NES. The dynamical equation is given, and the essential analytical investigation is ca...A parallel nonlinear energy sink(NES) is proposed and analyzed. The parallel NES is composed of a vibro-impact(VI) NES and a cubic NES. The dynamical equation is given, and the essential analytical investigation is carried out to deal with the cubic nonlinearity and impact nonlinearity. Multiple time-scale expansion is introduced, and the zeroth order is derived to give a rough outline of the system. The underlying Hamilton dynamic equation is given, and then the optimal stiffness is expressed. The clearance is regarded as a critical factor for the VI. Based on the periodical impact treatment by analytical investigation, the relationships of the cubic stiffness, the clearance, and the zeroth-order attenuation amplitude of the linear primary oscillator(LPO) are obtained.A cubic NES under the optimal condition is compared with the parallel NES. Harmonic signals, harmonic signals with noises, and the excitation generated by a second-order?lter are considered as the potential excitation forces on the system. The targeted energy transfer(TET) in the designed parallel NES is shown to be more e?cient.展开更多
To improve the low tracking precision caused by lagged filter gain or imprecise state noise when the target highly maneuvers, a modified unscented Kalman filter algorithm based on the improved filter gain and adaptive...To improve the low tracking precision caused by lagged filter gain or imprecise state noise when the target highly maneuvers, a modified unscented Kalman filter algorithm based on the improved filter gain and adaptive scale factor of state noise is presented. In every filter process, the estimated scale factor is used to update the state noise covariance Qk, and the improved filter gain is obtained in the filter process of unscented Kalman filter （UKF） via predicted variance Pk｜k-1, which is similar to the standard Kalman filter. Simulation results show that the proposed algorithm provides better accuracy and ability to adapt to the highly maneuvering target compared with the standard UKF.展开更多
Reasonable selection and optimization of a filter used in model estimation for a multiple model structure is the key to improve tracking accuracy of maneuvering target.Combining with the cubature Kalman filter with it...Reasonable selection and optimization of a filter used in model estimation for a multiple model structure is the key to improve tracking accuracy of maneuvering target.Combining with the cubature Kalman filter with iterated observation update and the interacting multiple model method,a novel interacting multiple model algorithm based on the cubature Kalman filter with observation iterated update is proposed.Firstly,aiming to the structural features of cubature Kalman filter,the cubature Kalman filter with observation iterated update is constructed by the mechanism of iterated observation update.Secondly,the improved cubature Kalman filter is used as the model filter of interacting multiple model,and the stability and reliability of model identification and state estimation are effectively promoted by the optimization of model filtering step.In the simulations,compared with classic improved interacting multiple model algorithms,the theoretical analysis and experimental results show the feasibility and validity of the proposed algorithm.展开更多
In the background of signal detection for high frequency （I/F） radar, the sea clutter is quite significant and can mask some weak target signals. A new clutter rejection method named “nonlinear projection” is give...In the background of signal detection for high frequency （I/F） radar, the sea clutter is quite significant and can mask some weak target signals. A new clutter rejection method named “nonlinear projection” is given to improve the SNR of the target. This approach is based on the recent observation that HF sea clutter may be modeled as a nonlinear deterministic dynamical system. After approximating the multidimensional reconstruction of the clutter by a low-dimensional attractor, projections onto this attractor can separate the clutter from other components. Real sea clutter, simulated target data and real target data are used to show that a nonlinear clutter rejection method is a promising technique to suppress sea clutter and enhances target detection.展开更多
As a new method for dealing with any nonlinear or non-Ganssian distributions, based on the Monte Carlo methods and Bayesian filtering, particle filters （PF） are favored by researchers and widely applied in many fiel...As a new method for dealing with any nonlinear or non-Ganssian distributions, based on the Monte Carlo methods and Bayesian filtering, particle filters （PF） are favored by researchers and widely applied in many fields. Based on particle filtering, an improved extended Kalman filter （EKF） proposal distribution is presented. Evaluation of the weights is simplified and other improved techniques including the residual resampling step and Markov Chain Monte Carlo method are introduced for target tracking. Performances of the EKF, basic PF and the improved PF are compared in target tracking examples. The simulation results confirm that the improved particle filter outperforms the others.展开更多
A marginalized particle filtering （MPF） approach is proposed for target tracking under the background of passive measurement. Essentially, the MPF is a combination of particle filtering technique and Kalman filter. ...A marginalized particle filtering （MPF） approach is proposed for target tracking under the background of passive measurement. Essentially, the MPF is a combination of particle filtering technique and Kalman filter. By making full use of marginalization, the distributions of the tractable linear part of the total state variables are updated analytically using Kalman filter, and only the lower-dimensional nonlinear state variable needs to be dealt with using particle filter. Simulation studies are performed on an illustrative example, and the results show that the MPF method leads to a significant reduction of the tracking errors when compared with the direct particle implementation. Real data test results also validate the effectiveness of the presented method.展开更多
For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter （EKF） proposal function is applied to ...For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter （EKF） proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo （MCMC） method, the resampling step, ere novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.展开更多
Recent advances in the application of the nonlinear energy sink under a sinusoidal excitation make it possible to investigate metal-rubber vibration absorber. To provide such a vibration absorber for the integrated sp...Recent advances in the application of the nonlinear energy sink under a sinusoidal excitation make it possible to investigate metal-rubber vibration absorber. To provide such a vibration absorber for the integrated spacecraft platform,we analyze the targeted energy transfer of the simplified model with nonlinear energy sink using the complex-variables averaging method. Theoretical study shows two quasi-periodic responses that are essentially different in this nonlinear system. The steady-state response which is one of two quasi-periodic responses is caused by the linear instability of system,and another one appears as a result of the nonlinear normal modes between the linear and nonlinear oscillators,resulting from the energy transfer of different oscillators,and it can be used to vibration absorber. Secondly,this paper also discusses the performance of the proposed nonlinear absorber by using the phase portraits. All conclusion derived by the analytic model is verified numerically and the results are consistent with numerical simulations.展开更多
This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantification theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal wit...This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantification theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal with the problem of mineral prediction without defining a training area. In mineral target prediction, the pre-defined statistical cells, such as grid cells, can be implicitly transformed using kernel techniques from input space to a high-dimensional feature space, where the nonlinearly separable clusters in the input space are expected to be linearly separable. Then, the transformed cells in the feature space are mapped by the fourth quantification theory onto a low-dimensional scaling space, where the scaled cells can be visually clustered according to their spatial locations. At the same time, those cells, which are far away from the cluster center of the majority of the scaled cells, are recognized as anomaly cells. Finally, whether the anomaly cells can serve as mineral potential target cells can be tested by spatially superimposing the known mineral occurrences onto the anomaly cells. A case study shows that nearly all the known mineral occurrences spatially coincide with the anomaly cells with nearly the smallest scaled coordinates in one-dimensional scaling space. In the case study, the mineral target cells delineated by the new model are similar to those predicted by the well-known WofE model.展开更多
基金supported by the Doctorial Innovation Fund (DY11104)the Aviation Science Innovation Fund of China (20090196005,20100196002)
文摘Based on the idea of zeroing the line of sight rate（LOSR）,a novel nonlinear differential geometric（DG） law for intercepting the agile target is proposed.In the first part,the DG formulations are utilized to describe the relatively kinematics model of missile and target,and the nonlinear DG guidance（DGG） law is proposed based on the nonlinear control theory to eliminate the influence brought by target.Further,the missile guidance commands are derived to overcome the information loss caused by decoupling condition,the new necessary initial condition is developed to guarantee capture the agile target.Then,the designed nonlinear DGG commands are transformed from an arc-length system to the time domain.A desirable aspect of the designed guidance law is that it does not require rigorous information about target acceleration.Representative numerical results show that the designed guidance law obtain a better performance than the traditional DGG law for agile target.
基金Project supported by the National Natural Science Foundation of China(Nos.11632011,11702170,11472170,51421092,and 11572189)
文摘A parallel nonlinear energy sink(NES) is proposed and analyzed. The parallel NES is composed of a vibro-impact(VI) NES and a cubic NES. The dynamical equation is given, and the essential analytical investigation is carried out to deal with the cubic nonlinearity and impact nonlinearity. Multiple time-scale expansion is introduced, and the zeroth order is derived to give a rough outline of the system. The underlying Hamilton dynamic equation is given, and then the optimal stiffness is expressed. The clearance is regarded as a critical factor for the VI. Based on the periodical impact treatment by analytical investigation, the relationships of the cubic stiffness, the clearance, and the zeroth-order attenuation amplitude of the linear primary oscillator(LPO) are obtained.A cubic NES under the optimal condition is compared with the parallel NES. Harmonic signals, harmonic signals with noises, and the excitation generated by a second-order?lter are considered as the potential excitation forces on the system. The targeted energy transfer(TET) in the designed parallel NES is shown to be more e?cient.
基金supported by the National Natural Science Fundationof China(61102109)
文摘To improve the low tracking precision caused by lagged filter gain or imprecise state noise when the target highly maneuvers, a modified unscented Kalman filter algorithm based on the improved filter gain and adaptive scale factor of state noise is presented. In every filter process, the estimated scale factor is used to update the state noise covariance Qk, and the improved filter gain is obtained in the filter process of unscented Kalman filter （UKF） via predicted variance Pk｜k-1, which is similar to the standard Kalman filter. Simulation results show that the proposed algorithm provides better accuracy and ability to adapt to the highly maneuvering target compared with the standard UKF.
基金Supported by the National Nature Science Foundations of China(No.61300214,U1204611,61170243)the Science and Technology Innovation Team Support Plan of Education Department of Henan Province(No.13IRTSTHN021)+3 种基金the Science and Technology Research Key Project of Education Department of Henan Province(No.13A413066)the Basic and Frontier Technology Research Plan of Henan Province(No.132300410148)the Funding Scheme of Young Key Teacher of Henan Province Universitiesthe Key Project of Teaching Reform Research of Henan University(No.HDXJJG2013-07)
文摘Reasonable selection and optimization of a filter used in model estimation for a multiple model structure is the key to improve tracking accuracy of maneuvering target.Combining with the cubature Kalman filter with iterated observation update and the interacting multiple model method,a novel interacting multiple model algorithm based on the cubature Kalman filter with observation iterated update is proposed.Firstly,aiming to the structural features of cubature Kalman filter,the cubature Kalman filter with observation iterated update is constructed by the mechanism of iterated observation update.Secondly,the improved cubature Kalman filter is used as the model filter of interacting multiple model,and the stability and reliability of model identification and state estimation are effectively promoted by the optimization of model filtering step.In the simulations,compared with classic improved interacting multiple model algorithms,the theoretical analysis and experimental results show the feasibility and validity of the proposed algorithm.
文摘In the background of signal detection for high frequency （I/F） radar, the sea clutter is quite significant and can mask some weak target signals. A new clutter rejection method named “nonlinear projection” is given to improve the SNR of the target. This approach is based on the recent observation that HF sea clutter may be modeled as a nonlinear deterministic dynamical system. After approximating the multidimensional reconstruction of the clutter by a low-dimensional attractor, projections onto this attractor can separate the clutter from other components. Real sea clutter, simulated target data and real target data are used to show that a nonlinear clutter rejection method is a promising technique to suppress sea clutter and enhances target detection.
基金Project supported by National High-Technology Research and De-velopment Program(Grant No .863 -2001AA422420-02)
文摘As a new method for dealing with any nonlinear or non-Ganssian distributions, based on the Monte Carlo methods and Bayesian filtering, particle filters （PF） are favored by researchers and widely applied in many fields. Based on particle filtering, an improved extended Kalman filter （EKF） proposal distribution is presented. Evaluation of the weights is simplified and other improved techniques including the residual resampling step and Markov Chain Monte Carlo method are introduced for target tracking. Performances of the EKF, basic PF and the improved PF are compared in target tracking examples. The simulation results confirm that the improved particle filter outperforms the others.
文摘A marginalized particle filtering （MPF） approach is proposed for target tracking under the background of passive measurement. Essentially, the MPF is a combination of particle filtering technique and Kalman filter. By making full use of marginalization, the distributions of the tractable linear part of the total state variables are updated analytically using Kalman filter, and only the lower-dimensional nonlinear state variable needs to be dealt with using particle filter. Simulation studies are performed on an illustrative example, and the results show that the MPF method leads to a significant reduction of the tracking errors when compared with the direct particle implementation. Real data test results also validate the effectiveness of the presented method.
基金This project was supported by the National Natural Science Foundation of China (50405017) .
文摘For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter （EKF） proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo （MCMC） method, the resampling step, ere novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.
基金Sponsored by the Open Fund of National Defense Key Discipline Laboratory of Micro-Spacecraft Technology(Grant No.HIT.KLOF.MST.201302)
文摘Recent advances in the application of the nonlinear energy sink under a sinusoidal excitation make it possible to investigate metal-rubber vibration absorber. To provide such a vibration absorber for the integrated spacecraft platform,we analyze the targeted energy transfer of the simplified model with nonlinear energy sink using the complex-variables averaging method. Theoretical study shows two quasi-periodic responses that are essentially different in this nonlinear system. The steady-state response which is one of two quasi-periodic responses is caused by the linear instability of system,and another one appears as a result of the nonlinear normal modes between the linear and nonlinear oscillators,resulting from the energy transfer of different oscillators,and it can be used to vibration absorber. Secondly,this paper also discusses the performance of the proposed nonlinear absorber by using the phase portraits. All conclusion derived by the analytic model is verified numerically and the results are consistent with numerical simulations.
基金supported by National Natural Science Foundation of China (No.40872193)
文摘This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantification theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal with the problem of mineral prediction without defining a training area. In mineral target prediction, the pre-defined statistical cells, such as grid cells, can be implicitly transformed using kernel techniques from input space to a high-dimensional feature space, where the nonlinearly separable clusters in the input space are expected to be linearly separable. Then, the transformed cells in the feature space are mapped by the fourth quantification theory onto a low-dimensional scaling space, where the scaled cells can be visually clustered according to their spatial locations. At the same time, those cells, which are far away from the cluster center of the majority of the scaled cells, are recognized as anomaly cells. Finally, whether the anomaly cells can serve as mineral potential target cells can be tested by spatially superimposing the known mineral occurrences onto the anomaly cells. A case study shows that nearly all the known mineral occurrences spatially coincide with the anomaly cells with nearly the smallest scaled coordinates in one-dimensional scaling space. In the case study, the mineral target cells delineated by the new model are similar to those predicted by the well-known WofE model.
