For ballistic mid-course targets,in addition to constant orbital motion,the target or any structure on the target undergoes micro-motion dynamics,such as spin,precession and tumbling.The micro-motion characteristics o...For ballistic mid-course targets,in addition to constant orbital motion,the target or any structure on the target undergoes micro-motion dynamics,such as spin,precession and tumbling.The micro-motion characteristics of the ballistic mid-course targets were discussed.The target motion model and inverse synthetic aperture radar(ISAR) imaging model for this kind of targets were built.Then,the influence of micro-motion on ISAR imaging based on the established imaging model was presented.The computer simulation to get mid-course target echoes from static darkroom electromagnetic scattering data based on the established target motion model was realized.The imaging results of computer simulation show the validity of ISAR imaging analysis for micro-motion targets.展开更多
The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)information.In this paper,a 3D ISAR imaging method for the space target is propos...The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)information.In this paper,a 3D ISAR imaging method for the space target is proposed based on mutliorbit observation data and an improved orthogonal matching pursuit(OMP)algorithm.Firstly,the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction dimension.Then,an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix data.Finally,scattering centers can be reconstructed with specific three dimensional locations.Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.展开更多
The issue of small-angle maneuvering targets inverse synthetic aperture radar(ISAR)imaging has been successfully addressed by popular motion compensation algorithms.However,when the target’s rotational velocity is su...The issue of small-angle maneuvering targets inverse synthetic aperture radar(ISAR)imaging has been successfully addressed by popular motion compensation algorithms.However,when the target’s rotational velocity is sufficiently high during the dwell time of the radar,such compensation algorithms cannot obtain a high quality image.This paper proposes an ISAR imaging algorithm based on keystone transform and deep learning algorithm.The keystone transform is used to coarsely compensate for the target’s rotational motion and translational motion,and the deep learning algorithm is used to achieve a super-resolution image.The uniformly distributed point target data are used as the data set of the training u-net network.In addition,this method does not require estimating the motion parameters of the target,which simplifies the algorithm steps.Finally,several experiments are performed to demonstrate the effectiveness of the proposed algorithm.展开更多
Inverse synthetic aperture radar （ISAR） imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-var...Inverse synthetic aperture radar （ISAR） imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-varying, which will degrade the ISAR image quality for the traditional range-Doppler （RD） algorithm. In this paper, the received signal in a range bin is characterized as the multi-component polynomial phase signal （PPS） after the motion compensation, and a new approach of time-frequency represen- tation, generalized polynomial Wigner-Ville distribution （GPWVD）, is proposed for the azimuth focusing. The GPWVD is based on the exponential matched-phase （EMP） principle. Compared with the conventional polynomial Wigner-Ville distribution （PWVD）, the EMP principle transfers the non-integer lag coefficients of the PWVD to the position of the exponential of the signal, and the interpolation can be avoided completely. For the GPWVD, the cross-terms between multi-component signals can be reduced by decomposing the GPWVD into the convolution of Wigner-Ville distribution （WVD） and the spectrum of phase adjust functions. The GPWVD is used in the ISAR imaging of ship targets, and the high quality instantaneous ISAR images can be obtained. Simulation results and measurement data demonstrate the effectiveness of the proposed new method.展开更多
The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal mod...The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal model of rotating target with fixed acceleration is presented and the weighted linear least squares estimation of rotational parameters with fixed velocity or acceleration is proposed via the relationship of cross-range FM （frequency modulation） parameter, scatterers coordinates and rotational parameters. The FM parameter is calculated via RWT （Radon-Wigner transform）. The ISAR imaging and cross-range scaling based on scaled RWT imaging method are implemented after obtaining rotational parameters. The rotational parameters estimation and cross-range scaling are validated by the ISAR processing of experimental radar data, and the method presents good application foreground to the ISAR imaging and scaling of maneuvering target.展开更多
Inverse synthetic aperture radar(ISAR)imaging of near-field targets is potentially useful in some specific applications,which makes it very important to efficiently produce highquality image of the near-field target.I...Inverse synthetic aperture radar(ISAR)imaging of near-field targets is potentially useful in some specific applications,which makes it very important to efficiently produce highquality image of the near-field target.In this paper,the simplified target model with uniform linear motion is applied to the near-field target imaging,which overcomes the complexity of the traditional near-field imaging algorithm.According to this signal model,the method based on coordinate conversion and image interpolation combined with the range-Doppler(R-D)algorithm is proposed to correct the near-field distortion problem.Compared with the back-projection(BP)algorithm,the proposed method produces better focused ISAR images of the near-field target,and decreases the computation complexity significantly.Experimental results of the simulated data have demonstrated the effectiveness and robustness of the proposed method.展开更多
Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high comp...Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high computational cost and poor imaging quality under a low signal to noise ratio (SNR) condition. This paper proposes a fast decoupled ISAR imaging method by exploiting the inherent structural sparse information of the targets. Firstly, the ISAR imaging problem is decoupled into two sub-problems. One is range direction imaging and the other is azimuth direction focusing. Secondly, an efficient two-stage SR method is proposed to obtain higher resolution range profiles by using jointly sparse information. Finally, the residual linear Bregman iteration via fast Fourier transforms (RLBI-FFT) is proposed to perform the azimuth focusing on low SNR efficiently. Theoretical analysis and simulation results show that the proposed method has better performence to efficiently implement higher-resolution ISAR imaging under the low SNR condition.展开更多
Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retr...Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed,which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler(RD) algorithm and oversampling smoothness(OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.展开更多
It is potentially useful to perform deception jamming using the digital image synthesizer （DIS） since it can form a two-dimensional （2D） decoy but suffers from multiple decoys ge- neration. Inspired by the intermi...It is potentially useful to perform deception jamming using the digital image synthesizer （DIS） since it can form a two-dimensional （2D） decoy but suffers from multiple decoys ge- neration. Inspired by the intermittent sampling repeater jamming （ISRJ）, the generation of inverse synthetic aperture radar （ISAR） decoys is addressed, associated with the DIS and the ISRJ. Radar pulses are sampled intermittently and modulated by the scatter- ing model of a false target by mounting the jammer on a moving platform, and then the jamming signals are retransmitted to the radar and a train of decoys are induced after ISAR imaging. A scattering model of Yak-42 is adopted as the false-target mo- dulation model to verify the effectiveness of the jamming method based on the standard ISAR motion compensation and image for- mation procedure.展开更多
基金Project(61360020102) supported by the National Basic Research Development Program of China
文摘For ballistic mid-course targets,in addition to constant orbital motion,the target or any structure on the target undergoes micro-motion dynamics,such as spin,precession and tumbling.The micro-motion characteristics of the ballistic mid-course targets were discussed.The target motion model and inverse synthetic aperture radar(ISAR) imaging model for this kind of targets were built.Then,the influence of micro-motion on ISAR imaging based on the established imaging model was presented.The computer simulation to get mid-course target echoes from static darkroom electromagnetic scattering data based on the established target motion model was realized.The imaging results of computer simulation show the validity of ISAR imaging analysis for micro-motion targets.
文摘The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)information.In this paper,a 3D ISAR imaging method for the space target is proposed based on mutliorbit observation data and an improved orthogonal matching pursuit(OMP)algorithm.Firstly,the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction dimension.Then,an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix data.Finally,scattering centers can be reconstructed with specific three dimensional locations.Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.
基金This work was supported by the National Natural Science Foundation of China(61571388,61871465,62071414)the Project of Introducing Overseas Students in Hebei Province(C20200367).
文摘The issue of small-angle maneuvering targets inverse synthetic aperture radar(ISAR)imaging has been successfully addressed by popular motion compensation algorithms.However,when the target’s rotational velocity is sufficiently high during the dwell time of the radar,such compensation algorithms cannot obtain a high quality image.This paper proposes an ISAR imaging algorithm based on keystone transform and deep learning algorithm.The keystone transform is used to coarsely compensate for the target’s rotational motion and translational motion,and the deep learning algorithm is used to achieve a super-resolution image.The uniformly distributed point target data are used as the data set of the training u-net network.In addition,this method does not require estimating the motion parameters of the target,which simplifies the algorithm steps.Finally,several experiments are performed to demonstrate the effectiveness of the proposed algorithm.
基金supported by the National Natural Science Foundation of China (61001166)the Specialized Research Fund for the Doctoral Program of Higher Education (20092302120002)+3 种基金the Aerospace Support Fund (2011-HT-HGD-16)the Fundamental Research Funds for the Central Universities (HIT.BRETIII.201207)the Postdoctoral ScienceResearch Developmental Foundation of Heilongjiang Province (LBHQ11092)the Heilongjiang Postdoctoral Specialized Research Fund
文摘Inverse synthetic aperture radar （ISAR） imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-varying, which will degrade the ISAR image quality for the traditional range-Doppler （RD） algorithm. In this paper, the received signal in a range bin is characterized as the multi-component polynomial phase signal （PPS） after the motion compensation, and a new approach of time-frequency represen- tation, generalized polynomial Wigner-Ville distribution （GPWVD）, is proposed for the azimuth focusing. The GPWVD is based on the exponential matched-phase （EMP） principle. Compared with the conventional polynomial Wigner-Ville distribution （PWVD）, the EMP principle transfers the non-integer lag coefficients of the PWVD to the position of the exponential of the signal, and the interpolation can be avoided completely. For the GPWVD, the cross-terms between multi-component signals can be reduced by decomposing the GPWVD into the convolution of Wigner-Ville distribution （WVD） and the spectrum of phase adjust functions. The GPWVD is used in the ISAR imaging of ship targets, and the high quality instantaneous ISAR images can be obtained. Simulation results and measurement data demonstrate the effectiveness of the proposed new method.
基金supported by the National Natural Science Foundation of China (60875019)
文摘The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal model of rotating target with fixed acceleration is presented and the weighted linear least squares estimation of rotational parameters with fixed velocity or acceleration is proposed via the relationship of cross-range FM （frequency modulation） parameter, scatterers coordinates and rotational parameters. The FM parameter is calculated via RWT （Radon-Wigner transform）. The ISAR imaging and cross-range scaling based on scaled RWT imaging method are implemented after obtaining rotational parameters. The rotational parameters estimation and cross-range scaling are validated by the ISAR processing of experimental radar data, and the method presents good application foreground to the ISAR imaging and scaling of maneuvering target.
基金supported by the National Natural Science Foundation of China(61871146).
文摘Inverse synthetic aperture radar(ISAR)imaging of near-field targets is potentially useful in some specific applications,which makes it very important to efficiently produce highquality image of the near-field target.In this paper,the simplified target model with uniform linear motion is applied to the near-field target imaging,which overcomes the complexity of the traditional near-field imaging algorithm.According to this signal model,the method based on coordinate conversion and image interpolation combined with the range-Doppler(R-D)algorithm is proposed to correct the near-field distortion problem.Compared with the back-projection(BP)algorithm,the proposed method produces better focused ISAR images of the near-field target,and decreases the computation complexity significantly.Experimental results of the simulated data have demonstrated the effectiveness and robustness of the proposed method.
基金supported by the National Natural Science Foundation of China(61671469)
文摘Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high computational cost and poor imaging quality under a low signal to noise ratio (SNR) condition. This paper proposes a fast decoupled ISAR imaging method by exploiting the inherent structural sparse information of the targets. Firstly, the ISAR imaging problem is decoupled into two sub-problems. One is range direction imaging and the other is azimuth direction focusing. Secondly, an efficient two-stage SR method is proposed to obtain higher resolution range profiles by using jointly sparse information. Finally, the residual linear Bregman iteration via fast Fourier transforms (RLBI-FFT) is proposed to perform the azimuth focusing on low SNR efficiently. Theoretical analysis and simulation results show that the proposed method has better performence to efficiently implement higher-resolution ISAR imaging under the low SNR condition.
基金supported by the National Natural Science Foundation of China(6157138861601398)the National Natural Science Foundation of Hebei Province(F2016203251)
文摘Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed,which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler(RD) algorithm and oversampling smoothness(OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.
基金supported by the National Natural Science Foundation of China(6137217061401491)
文摘It is potentially useful to perform deception jamming using the digital image synthesizer （DIS） since it can form a two-dimensional （2D） decoy but suffers from multiple decoys ge- neration. Inspired by the intermittent sampling repeater jamming （ISRJ）, the generation of inverse synthetic aperture radar （ISAR） decoys is addressed, associated with the DIS and the ISRJ. Radar pulses are sampled intermittently and modulated by the scatter- ing model of a false target by mounting the jammer on a moving platform, and then the jamming signals are retransmitted to the radar and a train of decoys are induced after ISAR imaging. A scattering model of Yak-42 is adopted as the false-target mo- dulation model to verify the effectiveness of the jamming method based on the standard ISAR motion compensation and image for- mation procedure.
