The parametric scattering center model of radar tar-get has the advantages of simplicity,sparsity and mechanism relevant,making it widely applied in fields such as radar data compression and rapid generation,radar ima...The parametric scattering center model of radar tar-get has the advantages of simplicity,sparsity and mechanism relevant,making it widely applied in fields such as radar data compression and rapid generation,radar imaging,feature extraction and recognition.This paper summarizes and analyzes the research situation,development trend,and difficult prob-lems on scattering center(SC)parametric modeling from three aspects:parametric representation,determination method of model parameters,and application.展开更多
A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of...A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.展开更多
Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotio...Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.展开更多
The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs wi...The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs with strong scattering contributions.This paper presents an SC modeling approach to acquire the weak SCs of LDTs.We employ the induced currents at the LDT to search SCs,and the joint time-frequency transform together with the Hough transform to separate the scattering contributions of different SCs.Particle swarm optimization(PSO)is applied to improve the estimation results of SCs.The accuracy of the SC model built by this approach is verified by a full-wave numerical method.The validation results show that the SC model of the LDT can precisely simulate the signatures of high-resolution images,such as high-resolution range profile and inverse synthetic aperture radar(ISAR)images.展开更多
Parameter estimation of the attributed scattering center(ASC) model is significant for automatic target recognition(ATR). Sparse representation based parameter estimation methods have developed rapidly. Construction o...Parameter estimation of the attributed scattering center(ASC) model is significant for automatic target recognition(ATR). Sparse representation based parameter estimation methods have developed rapidly. Construction of the separable dictionary is a key issue for sparse representation technology. A compressive time-domain dictionary(TD) for ASC model is presented. Two-dimensional frequency domain responses of the ASC are produced and transformed into the time domain. Then these time domain responses are cutoff and stacked into vectors. These vectored time-domain responses are amalgamated to form the TD. Compared with the traditional frequency-domain dictionary(FD), the TD is a matrix that is quite spare and can markedly reduce the data size of the dictionary. Based on the basic TD construction method, we present four extended TD construction methods, which are available for different applications. In the experiments, the performance of the TD, including the basic model and the extended models, has been firstly analyzed in comparison with the FD. Secondly, an example of parameter estimation from SAR synthetic aperture radar(SAR) measurements of a target collected in an anechoic room is exhibited. Finally, a sparse image reconstruction example is from two apart apertures. Experimental results demonstrate the effectiveness and efficiency of the proposed TD.展开更多
The sparse recovery algorithms formulate synthetic aperture radar （SAR） imaging problem in terms of sparse representation （SR） of a small number of strong scatters＇ positions among a much large number of potentia...The sparse recovery algorithms formulate synthetic aperture radar （SAR） imaging problem in terms of sparse representation （SR） of a small number of strong scatters＇ positions among a much large number of potential scatters＇ positions, and provide an effective approach to improve the SAR image resolution. Based on the attributed scatter center model, several experiments were performed with different practical considerations to evaluate the performance of five representative SR techniques, namely, sparse Bayesian learning （SBL）, fast Bayesian matching pursuit （FBMP）, smoothed 10 norm method （SL0）, sparse reconstruction by separable approximation （SpaRSA）, fast iterative shrinkage-thresholding algorithm （FISTA）, and the parameter settings in five SR algorithms were discussed. In different situations, the performances of these algorithms were also discussed. Through the comparison of MSE and failure rate in each algorithm simulation, FBMP and SpaRSA are found suitable for dealing with problems in the SAR imaging based on attributed scattering center model. Although the SBL is time-consuming, it always get better performance when related to failure rate and high SNR.展开更多
基于典型地面背景电磁散射特性的研究,提出了介质粗糙地面上目标散射中心正向建模的方法。首先,通过蒙特卡罗方法随机生成粗糙面,利用高斯谱模拟三维粗糙地面模型,采用介电常数对不同地面材料进行表征;然后,采用正向途径并结合射线追踪...基于典型地面背景电磁散射特性的研究,提出了介质粗糙地面上目标散射中心正向建模的方法。首先,通过蒙特卡罗方法随机生成粗糙面,利用高斯谱模拟三维粗糙地面模型,采用介电常数对不同地面材料进行表征;然后,采用正向途径并结合射线追踪、分集技术将复杂的地面环境与MSTAR(Moving and Stationary Target Acquisition and Recognition)库中的BMP2步兵战车目标模型的整体散射离散为多个散射源的集合,再结合粗糙地面的不同介电常数进行分析,利用高频近似方法进行求解;最后,通过重构的合成孔径雷达(synthetic aperture radar,SAR)图像与MSTAR库实测数据集对比进行验证。结果表明,本文提出的介质粗糙地面上目标散射中心正向建模方法能够提高与实测图像数据的相似度,验证了其有效性。展开更多
On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high ...On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.展开更多
The noise robustness and parameter estimation performance of the classical three-dimensional estimating signal parameter via rotational invariance techniques(3D-ESPRIT)algorithm are poor when the parameters of the geo...The noise robustness and parameter estimation performance of the classical three-dimensional estimating signal parameter via rotational invariance techniques(3D-ESPRIT)algorithm are poor when the parameters of the geometric theory of the diffraction(GTD)model are estimated at low signal-to-noise ratio(SNR).To solve this problem,a modified 3D-ESPRIT algorithm is proposed.The modified algorithm improves the parameter estimation accuracy by proposing a novel spatial smoothing technique.Firstly,we make cross-correlation of the auto-correlation matrices;then by averaging the cross-correlation matrices of the forward and backward spatial smoothing,we can obtain a novel equivalent spatial smoothing matrix.The formula of the modified algorithm is derived and the performance of this improved method is also analyzed.Then we compare root-meansquare-errors(RMSEs)of different parameters and the locating accuracy obtained by different algorithms.Furthermore,radar cross section(RCS)of radar targets is extrapolated.Simulation results verify the effectiveness and superiority of the modified 3DESPRIT algorithm.展开更多
A research is done for multipath effects of low-angle tracking in meter-wave radar, and the theory of multi-scattering centers of complex target is discussed as well as the character of reflected echoes. This points o...A research is done for multipath effects of low-angle tracking in meter-wave radar, and the theory of multi-scattering centers of complex target is discussed as well as the character of reflected echoes. This points out that the distribution and scattering properties of scattering centers are the prime reasons which cause the variation of muhipath effects, and all the changes of position, motion and attitude of the target can influence the muhipath effects. By building of muhipath model for multi-scattering centers for target, the analysis above is verified and a new method of elevation estimation for low-angle target is presented. The new method uses canceling vectors obtained by searching to cancel reflected waves in echoes and reduce the influence of reflected com- ponents, which can improve the accuracy of elevation estimation of low-angle target and the performance of low- angle tracking in meter-wave radar. Experimental results verify the availability of the method.展开更多
多尺度非均匀背景为不同尺度和形状且在空间上分布不均匀的粗糙结构。本文针对多尺度非均匀粗糙背景散射特性快速计算问题,提出了基于散射中心方法的参数化表征模型。多尺度非均匀背景的散射场一般由地表大尺度表面所产生的镜反射分量...多尺度非均匀背景为不同尺度和形状且在空间上分布不均匀的粗糙结构。本文针对多尺度非均匀粗糙背景散射特性快速计算问题,提出了基于散射中心方法的参数化表征模型。多尺度非均匀背景的散射场一般由地表大尺度表面所产生的镜反射分量、大尺度表面几何不连续处所产生的绕射分量和地表小尺度粗糙面引起的漫散射分量共同组成。传统雷达目标散射中心建模采用分布型、局部型和滑动型散射中心模型(scattering center model, SCM)表征目标的反射和绕射散射;但是,传统散射中心表征形式仅能描述大尺度光滑表面、几何不连续处的散射场,无法描述小尺度粗糙面的散射效应。本文结合粗糙面的相干-非相干散射理论,在大尺度地形散射中心表征模型的基础上,利用相干模型修正小尺度粗糙面对大尺度表面散射场幅度的影响;利用双向反射分布函数(bidirectional reflectance distribution function, BRDF)建立非相干散射的参数化表征形式。对两种非均匀多尺度背景的散射特性进行参数化表征,并采用商业软件高频求解器对计算结果的精度和效率进行了校验,证明了粗糙背景散射中心参数化建模方法的可行性。展开更多
现有基于深度神经网络的高距离分辨(High Range Resolution,HRR)雷达目标识别方法是纯数据驱动模型,是1个飞行事故记录器结构,特征不具可解释性,在方位缺失情况下特征泛化性差,模型识别率急剧下降.对此,本文设计了一种物理可解释自编码...现有基于深度神经网络的高距离分辨(High Range Resolution,HRR)雷达目标识别方法是纯数据驱动模型,是1个飞行事故记录器结构,特征不具可解释性,在方位缺失情况下特征泛化性差,模型识别率急剧下降.对此,本文设计了一种物理可解释自编码模型(Physical Interpretable Auto-Encoder Model,PIAEM),解码网络结合雷达目标的散射点模型,利用编码网络挖掘雷达数据具有明确物理含义的散射中心特征,从成像角度描述目标的物理结构特性,如尺寸、轮廓等,在方位缺失情况下具有稳健的物理特性.设计了基于最小重构误差的分类准则,实现雷达目标识别.基于实测高距离分辨雷达回波数据的实验结果表明,本文方法提取的特征具有明确物理含义,且在方位缺失4/5的情况下,PIAEM比现有基于传统目标识别方法的准确率提升了10.27%,验证了本文方法具有方位稳健识别性能.展开更多
基金supported by the National Natural Science Foundation of China(62231001).
文摘The parametric scattering center model of radar tar-get has the advantages of simplicity,sparsity and mechanism relevant,making it widely applied in fields such as radar data compression and rapid generation,radar imaging,feature extraction and recognition.This paper summarizes and analyzes the research situation,development trend,and difficult prob-lems on scattering center(SC)parametric modeling from three aspects:parametric representation,determination method of model parameters,and application.
文摘A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation for Young Scientists of China (61101182)
文摘Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.
基金This work was supported by the National Key R&D Program of China(2017YFB0202500)the National Natural Science Foundation of China(61771052).
文摘The scattering centers(SCs)of low-detectable targets(LDTs)have a low scattering intensity.It is difficult to build the SC model of an LDT using the existing methods because these methods mainly concern dominant SCs with strong scattering contributions.This paper presents an SC modeling approach to acquire the weak SCs of LDTs.We employ the induced currents at the LDT to search SCs,and the joint time-frequency transform together with the Hough transform to separate the scattering contributions of different SCs.Particle swarm optimization(PSO)is applied to improve the estimation results of SCs.The accuracy of the SC model built by this approach is verified by a full-wave numerical method.The validation results show that the SC model of the LDT can precisely simulate the signatures of high-resolution images,such as high-resolution range profile and inverse synthetic aperture radar(ISAR)images.
基金Project(NCET-11-0866)supported by Education Ministry's new Century Excellent Talents Supporting Plan,China
文摘Parameter estimation of the attributed scattering center(ASC) model is significant for automatic target recognition(ATR). Sparse representation based parameter estimation methods have developed rapidly. Construction of the separable dictionary is a key issue for sparse representation technology. A compressive time-domain dictionary(TD) for ASC model is presented. Two-dimensional frequency domain responses of the ASC are produced and transformed into the time domain. Then these time domain responses are cutoff and stacked into vectors. These vectored time-domain responses are amalgamated to form the TD. Compared with the traditional frequency-domain dictionary(FD), the TD is a matrix that is quite spare and can markedly reduce the data size of the dictionary. Based on the basic TD construction method, we present four extended TD construction methods, which are available for different applications. In the experiments, the performance of the TD, including the basic model and the extended models, has been firstly analyzed in comparison with the FD. Secondly, an example of parameter estimation from SAR synthetic aperture radar(SAR) measurements of a target collected in an anechoic room is exhibited. Finally, a sparse image reconstruction example is from two apart apertures. Experimental results demonstrate the effectiveness and efficiency of the proposed TD.
基金Project(61171133)supported by the National Natural Science Foundation of ChinaProject(11JJ1010)supported by the Natural Science Fund for Distinguished Young Scholars of Hunan Province,ChinaProject(61101182)supported by National Natural Science Foundation for Young Scientists of China
文摘The sparse recovery algorithms formulate synthetic aperture radar （SAR） imaging problem in terms of sparse representation （SR） of a small number of strong scatters＇ positions among a much large number of potential scatters＇ positions, and provide an effective approach to improve the SAR image resolution. Based on the attributed scatter center model, several experiments were performed with different practical considerations to evaluate the performance of five representative SR techniques, namely, sparse Bayesian learning （SBL）, fast Bayesian matching pursuit （FBMP）, smoothed 10 norm method （SL0）, sparse reconstruction by separable approximation （SpaRSA）, fast iterative shrinkage-thresholding algorithm （FISTA）, and the parameter settings in five SR algorithms were discussed. In different situations, the performances of these algorithms were also discussed. Through the comparison of MSE and failure rate in each algorithm simulation, FBMP and SpaRSA are found suitable for dealing with problems in the SAR imaging based on attributed scattering center model. Although the SBL is time-consuming, it always get better performance when related to failure rate and high SNR.
文摘基于典型地面背景电磁散射特性的研究,提出了介质粗糙地面上目标散射中心正向建模的方法。首先,通过蒙特卡罗方法随机生成粗糙面,利用高斯谱模拟三维粗糙地面模型,采用介电常数对不同地面材料进行表征;然后,采用正向途径并结合射线追踪、分集技术将复杂的地面环境与MSTAR(Moving and Stationary Target Acquisition and Recognition)库中的BMP2步兵战车目标模型的整体散射离散为多个散射源的集合,再结合粗糙地面的不同介电常数进行分析,利用高频近似方法进行求解;最后,通过重构的合成孔径雷达(synthetic aperture radar,SAR)图像与MSTAR库实测数据集对比进行验证。结果表明,本文提出的介质粗糙地面上目标散射中心正向建模方法能够提高与实测图像数据的相似度,验证了其有效性。
文摘On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.
基金This work was supported by the National Natural Science Foundation of China(61372033).
文摘The noise robustness and parameter estimation performance of the classical three-dimensional estimating signal parameter via rotational invariance techniques(3D-ESPRIT)algorithm are poor when the parameters of the geometric theory of the diffraction(GTD)model are estimated at low signal-to-noise ratio(SNR).To solve this problem,a modified 3D-ESPRIT algorithm is proposed.The modified algorithm improves the parameter estimation accuracy by proposing a novel spatial smoothing technique.Firstly,we make cross-correlation of the auto-correlation matrices;then by averaging the cross-correlation matrices of the forward and backward spatial smoothing,we can obtain a novel equivalent spatial smoothing matrix.The formula of the modified algorithm is derived and the performance of this improved method is also analyzed.Then we compare root-meansquare-errors(RMSEs)of different parameters and the locating accuracy obtained by different algorithms.Furthermore,radar cross section(RCS)of radar targets is extrapolated.Simulation results verify the effectiveness and superiority of the modified 3DESPRIT algorithm.
文摘A research is done for multipath effects of low-angle tracking in meter-wave radar, and the theory of multi-scattering centers of complex target is discussed as well as the character of reflected echoes. This points out that the distribution and scattering properties of scattering centers are the prime reasons which cause the variation of muhipath effects, and all the changes of position, motion and attitude of the target can influence the muhipath effects. By building of muhipath model for multi-scattering centers for target, the analysis above is verified and a new method of elevation estimation for low-angle target is presented. The new method uses canceling vectors obtained by searching to cancel reflected waves in echoes and reduce the influence of reflected com- ponents, which can improve the accuracy of elevation estimation of low-angle target and the performance of low- angle tracking in meter-wave radar. Experimental results verify the availability of the method.
文摘多尺度非均匀背景为不同尺度和形状且在空间上分布不均匀的粗糙结构。本文针对多尺度非均匀粗糙背景散射特性快速计算问题,提出了基于散射中心方法的参数化表征模型。多尺度非均匀背景的散射场一般由地表大尺度表面所产生的镜反射分量、大尺度表面几何不连续处所产生的绕射分量和地表小尺度粗糙面引起的漫散射分量共同组成。传统雷达目标散射中心建模采用分布型、局部型和滑动型散射中心模型(scattering center model, SCM)表征目标的反射和绕射散射;但是,传统散射中心表征形式仅能描述大尺度光滑表面、几何不连续处的散射场,无法描述小尺度粗糙面的散射效应。本文结合粗糙面的相干-非相干散射理论,在大尺度地形散射中心表征模型的基础上,利用相干模型修正小尺度粗糙面对大尺度表面散射场幅度的影响;利用双向反射分布函数(bidirectional reflectance distribution function, BRDF)建立非相干散射的参数化表征形式。对两种非均匀多尺度背景的散射特性进行参数化表征,并采用商业软件高频求解器对计算结果的精度和效率进行了校验,证明了粗糙背景散射中心参数化建模方法的可行性。
