Mechanical vibration of target structures will modulate the phase function of radar backscattering,and will induce the frequency modulation of returned signals from the target. It generates a side bands of the target ...Mechanical vibration of target structures will modulate the phase function of radar backscattering,and will induce the frequency modulation of returned signals from the target. It generates a side bands of the target body Doppler frequency shift,which is helpful for target recognition. Based on this,a micro-Doppler atomic storehouse is built for the target recognition,and four kinds of common classifiers are used separately to perform the classified recognition. The simulation experimental results show that this method has high recognition rate above 90%.展开更多
High resolution range imaging with correlation processing suffers from high sidelobe pedestal in random frequency-hopping wideband radar. After the factors which affect the sidelobe pedestal being analyzed, a compress...High resolution range imaging with correlation processing suffers from high sidelobe pedestal in random frequency-hopping wideband radar. After the factors which affect the sidelobe pedestal being analyzed, a compressed sensing based algorithm for high resolution range imaging and a new minimized ll-norm criterion for motion compensation are proposed. The random hopping of the transmitted carrier frequency is converted to restricted isometry property of the observing matrix. Then practical problems of imaging model solution and signal parameter design are resolved. Due to the particularity of the proposed algorithm, two new indicators of range profile, i.e., average signal to sidelobe ratio and local similarity, are defined. The chamber measured data are adopted to testify the validity of the proposed algorithm, and simulations are performed to analyze the precision of velocity measurement as well as the performance of motion compensation. The simulation results show that the proposed algorithm has such advantages as high precision velocity measurement, low sidelobe and short period imaging, which ensure robust imaging for moving targets when signal-to-noise ratio is above 10 dB.展开更多
This paper presents a joint method of Doppler Beam Sharpen (DBS) imaging and Signal Subspace Processing (SSP) to achieve Ground Moving Target Indication(GMTI) for along- track dual-antenna airborne radar. When the err...This paper presents a joint method of Doppler Beam Sharpen (DBS) imaging and Signal Subspace Processing (SSP) to achieve Ground Moving Target Indication(GMTI) for along- track dual-antenna airborne radar. When the error of the two antennas (also refers to channels) changes pulse to pulse, the method SSP is used to precisely calibrate the two antennas’ DBS images, then to detect the ground moving targets in the difference image of the two calibrated images. The method DBS-SSP is proved to offer performance improvement on the actually measured data and simulated data.展开更多
A real extended scene and moving targets multi-channel Synthetic Aperture Radar(SAR) raw signal simulator accounting for Inertial Navigation System(INS) errors and antenna patterns is presented in this paper. INS erro...A real extended scene and moving targets multi-channel Synthetic Aperture Radar(SAR) raw signal simulator accounting for Inertial Navigation System(INS) errors and antenna patterns is presented in this paper. INS errors are obtained by solving INS error differential equations with Runge-Kutta method. A high resolution SAR image is used to estimate the complex reflectance of real extended scene. Extended scene and moving target are simulated separately and then are superposed in time domain. The simulated multi-channel SAR data can be used for development of multi-channel SAR Ground Moving Target Indication(SAR-GMTI) and also can be used for development of SAR motion compensation.展开更多
The ground penetrating radar （GPR） detection data is a wide band signal, always disturbed by some noise, such as ambient random noise and muhiple refleetion waves. The noise affects the target identification of unde...The ground penetrating radar （GPR） detection data is a wide band signal, always disturbed by some noise, such as ambient random noise and muhiple refleetion waves. The noise affects the target identification of underground medium seriously. A method based on principal component analysis （PCA） was proposed to ex- tract the target signal and remove the uncorrelated noise. According to the correlation of signal, the authors get the eigenvalues and corresponding eigenvectors by decomposing the covariance matrix of GPR data and make linear transformation for the GPR data to get the principal components （PCs）. The lower-order PCs stand h^r the strong correlated target signals of the raw data, and the higher-order ones present the uneorrelated noise. Thus the authors can extract the target signal and filter uncorrelated noise effectively by the PCA. This method was demonstrated on real ultra-wideband through-wall radar data and simulated GPR data. Both of the results show that the PCA method can effectively extract the GPR target signal and remove the uncorrelated noise.展开更多
基金the foundation of doctor academic degree from Education Minirstry of China (20060699024)
文摘Mechanical vibration of target structures will modulate the phase function of radar backscattering,and will induce the frequency modulation of returned signals from the target. It generates a side bands of the target body Doppler frequency shift,which is helpful for target recognition. Based on this,a micro-Doppler atomic storehouse is built for the target recognition,and four kinds of common classifiers are used separately to perform the classified recognition. The simulation experimental results show that this method has high recognition rate above 90%.
基金Project(61171133) supported by the National Natural Science Foundation of ChinaProject(CX2011B019) supported by Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject(B110404) supported by Innovation Foundation for Outstanding Postgraduates of National University of Defense Technology,China
文摘High resolution range imaging with correlation processing suffers from high sidelobe pedestal in random frequency-hopping wideband radar. After the factors which affect the sidelobe pedestal being analyzed, a compressed sensing based algorithm for high resolution range imaging and a new minimized ll-norm criterion for motion compensation are proposed. The random hopping of the transmitted carrier frequency is converted to restricted isometry property of the observing matrix. Then practical problems of imaging model solution and signal parameter design are resolved. Due to the particularity of the proposed algorithm, two new indicators of range profile, i.e., average signal to sidelobe ratio and local similarity, are defined. The chamber measured data are adopted to testify the validity of the proposed algorithm, and simulations are performed to analyze the precision of velocity measurement as well as the performance of motion compensation. The simulation results show that the proposed algorithm has such advantages as high precision velocity measurement, low sidelobe and short period imaging, which ensure robust imaging for moving targets when signal-to-noise ratio is above 10 dB.
文摘This paper presents a joint method of Doppler Beam Sharpen (DBS) imaging and Signal Subspace Processing (SSP) to achieve Ground Moving Target Indication(GMTI) for along- track dual-antenna airborne radar. When the error of the two antennas (also refers to channels) changes pulse to pulse, the method SSP is used to precisely calibrate the two antennas’ DBS images, then to detect the ground moving targets in the difference image of the two calibrated images. The method DBS-SSP is proved to offer performance improvement on the actually measured data and simulated data.
文摘A real extended scene and moving targets multi-channel Synthetic Aperture Radar(SAR) raw signal simulator accounting for Inertial Navigation System(INS) errors and antenna patterns is presented in this paper. INS errors are obtained by solving INS error differential equations with Runge-Kutta method. A high resolution SAR image is used to estimate the complex reflectance of real extended scene. Extended scene and moving target are simulated separately and then are superposed in time domain. The simulated multi-channel SAR data can be used for development of multi-channel SAR Ground Moving Target Indication(SAR-GMTI) and also can be used for development of SAR motion compensation.
基金Supported by project of Natural Science Foundation of China(No.41174097)
文摘The ground penetrating radar （GPR） detection data is a wide band signal, always disturbed by some noise, such as ambient random noise and muhiple refleetion waves. The noise affects the target identification of underground medium seriously. A method based on principal component analysis （PCA） was proposed to ex- tract the target signal and remove the uncorrelated noise. According to the correlation of signal, the authors get the eigenvalues and corresponding eigenvectors by decomposing the covariance matrix of GPR data and make linear transformation for the GPR data to get the principal components （PCs）. The lower-order PCs stand h^r the strong correlated target signals of the raw data, and the higher-order ones present the uneorrelated noise. Thus the authors can extract the target signal and filter uncorrelated noise effectively by the PCA. This method was demonstrated on real ultra-wideband through-wall radar data and simulated GPR data. Both of the results show that the PCA method can effectively extract the GPR target signal and remove the uncorrelated noise.
