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
In order to improve the identification capability of ultra wide-band radar,this paper in-troduces a step-variant multiresolution approach for the time-shift parameter estimation. Subsequently,combining with the approa...In order to improve the identification capability of ultra wide-band radar,this paper in-troduces a step-variant multiresolution approach for the time-shift parameter estimation. Subsequently,combining with the approach,a Geometrical Theory of Diffraction(GTD) model-based time-shift Invariant method to target identification using Matching Pursuits and Likelihood Ratio Test(IMPLRT) is developed. Simulation results using measured scattering signatures of two targets in an ultra wide-band chamber are presented contrasting the performance of the IMPLRT to the Wang's MPLRT technique.展开更多
The Bayesian method is applied to the joint model selection and parameter estimation problem of the GTD model. An algorithm based on RJ-MCMC is designed. This algorithm not only improves the model order selection and ...The Bayesian method is applied to the joint model selection and parameter estimation problem of the GTD model. An algorithm based on RJ-MCMC is designed. This algorithm not only improves the model order selection and parameter estimation accuracy by exploiting the priori information of the GTD model, but also solves the mixed parameter estimation problem of the GTD model properly. Its performance is tested using numerical simulations and data generated by electromagnetic code. It is shown that it gives good model order selection and parameter estimation results, especially for low SNR, closely-spaced components and short data situations.展开更多
现代谱估计方法能够反演基于几何绕射理论(geometric theory of diffraction,GTD)的模型参数,但不能处理非均匀不完备的雷达散射截面(radar cross section,RCS)数据。此外,通过暗室测量获取完备的RCS数据也需要较大的时空开销。针对上...现代谱估计方法能够反演基于几何绕射理论(geometric theory of diffraction,GTD)的模型参数,但不能处理非均匀不完备的雷达散射截面(radar cross section,RCS)数据。此外,通过暗室测量获取完备的RCS数据也需要较大的时空开销。针对上述问题,提出一种基于迭代加权最小二乘(iteratively reweighed least squares,IRLS)的跳频模式下GTD散射参数提取和RCS重构方法。该方法将稀疏重构理论与GTD散射模型相结合,能够在RCS数据非均匀不完备的条件下反演散射参数和实现RCS重构。仿真数据和电磁计算数据用于验证所提方法的有效性,实验结果表明该方法对降低暗室步进频率RCS的测量成本和扩增雷达RCS数据具有重要意义。展开更多
多视角多频带逆合成孔径雷达(inverse synthetic aperture radar,ISAR)融合成像技术克服了单雷达成像分辨率受发射带宽和观测视角的限制,是提高ISAR成像的二维分辨率的新手段。在宽带小角度观测条件下,针对目标散射系数随频率变化的情况...多视角多频带逆合成孔径雷达(inverse synthetic aperture radar,ISAR)融合成像技术克服了单雷达成像分辨率受发射带宽和观测视角的限制,是提高ISAR成像的二维分辨率的新手段。在宽带小角度观测条件下,针对目标散射系数随频率变化的情况,提出一种基于几何绕射理论(geometrical theory of diffraction,GTD)模型的多视角多频带ISAR融合成像方法。首先,以GTD模型为基础建立ISAR成像回波模型;然后,将多视角多频带ISAR融合成像问题转化为信号稀疏重构问题,并采用正交匹配追踪算法求解,在保证融合成像质量的同时提高了的成像效率;最后,利用仿真实验验证了所提方法的有效性。展开更多
几何绕射理论(Geometrical Theory of Diffraction,GTD)模型能够精确描述高频区雷达目标的电磁散射机理。该文在分析雷达回波稀疏特性的基础上,将参数估计问题转化为压缩感知理论中的稀疏信号重构问题,据此提出了一种基于压缩感知的2维...几何绕射理论(Geometrical Theory of Diffraction,GTD)模型能够精确描述高频区雷达目标的电磁散射机理。该文在分析雷达回波稀疏特性的基础上,将参数估计问题转化为压缩感知理论中的稀疏信号重构问题,据此提出了一种基于压缩感知的2维GTD模型参数估计方法。该方法首先利用2维傅里叶变换成像确定目标散射中心的支撑区域,然后在支撑区域内对散射中心的GTD参数进行估计,最后利用聚类方法和最小二乘方法对估计结果进行修正。仿真和暗室测量数据实验结果表明,与现有方法相比,所提方法能有效改善模型参数的估计性能,且对提高散射中心类型参数的估计精度更为明显。展开更多
研究了窄带雷达信号融合问题,提出了一种基于GTD(Geometrical Theory of Diffraction)模型的窄带雷达信号多视角多波段融合的方法。在同波段多视角融合方面,利用Lincoln实验室的方法给出模型参数的初值,再运用遗传算法对参数进行迭代寻...研究了窄带雷达信号融合问题,提出了一种基于GTD(Geometrical Theory of Diffraction)模型的窄带雷达信号多视角多波段融合的方法。在同波段多视角融合方面,利用Lincoln实验室的方法给出模型参数的初值,再运用遗传算法对参数进行迭代寻优。而在不同波段多视角融合方面,则利用视角融合后获得的同角度不同波段窄带信号联合估计频率衰减因子。并通过仿真实验以二维条带目标为例验证了方法的有效性。展开更多
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In order to improve the identification capability of ultra wide-band radar,this paper in-troduces a step-variant multiresolution approach for the time-shift parameter estimation. Subsequently,combining with the approach,a Geometrical Theory of Diffraction(GTD) model-based time-shift Invariant method to target identification using Matching Pursuits and Likelihood Ratio Test(IMPLRT) is developed. Simulation results using measured scattering signatures of two targets in an ultra wide-band chamber are presented contrasting the performance of the IMPLRT to the Wang's MPLRT technique.
基金Supported by the National "973" Key Basic Research Project (Grant No. 51314)
文摘The Bayesian method is applied to the joint model selection and parameter estimation problem of the GTD model. An algorithm based on RJ-MCMC is designed. This algorithm not only improves the model order selection and parameter estimation accuracy by exploiting the priori information of the GTD model, but also solves the mixed parameter estimation problem of the GTD model properly. Its performance is tested using numerical simulations and data generated by electromagnetic code. It is shown that it gives good model order selection and parameter estimation results, especially for low SNR, closely-spaced components and short data situations.
文摘现代谱估计方法能够反演基于几何绕射理论(geometric theory of diffraction,GTD)的模型参数,但不能处理非均匀不完备的雷达散射截面(radar cross section,RCS)数据。此外,通过暗室测量获取完备的RCS数据也需要较大的时空开销。针对上述问题,提出一种基于迭代加权最小二乘(iteratively reweighed least squares,IRLS)的跳频模式下GTD散射参数提取和RCS重构方法。该方法将稀疏重构理论与GTD散射模型相结合,能够在RCS数据非均匀不完备的条件下反演散射参数和实现RCS重构。仿真数据和电磁计算数据用于验证所提方法的有效性,实验结果表明该方法对降低暗室步进频率RCS的测量成本和扩增雷达RCS数据具有重要意义。
文摘多视角多频带逆合成孔径雷达(inverse synthetic aperture radar,ISAR)融合成像技术克服了单雷达成像分辨率受发射带宽和观测视角的限制,是提高ISAR成像的二维分辨率的新手段。在宽带小角度观测条件下,针对目标散射系数随频率变化的情况,提出一种基于几何绕射理论(geometrical theory of diffraction,GTD)模型的多视角多频带ISAR融合成像方法。首先,以GTD模型为基础建立ISAR成像回波模型;然后,将多视角多频带ISAR融合成像问题转化为信号稀疏重构问题,并采用正交匹配追踪算法求解,在保证融合成像质量的同时提高了的成像效率;最后,利用仿真实验验证了所提方法的有效性。
文摘几何绕射理论(Geometrical Theory of Diffraction,GTD)模型能够精确描述高频区雷达目标的电磁散射机理。该文在分析雷达回波稀疏特性的基础上,将参数估计问题转化为压缩感知理论中的稀疏信号重构问题,据此提出了一种基于压缩感知的2维GTD模型参数估计方法。该方法首先利用2维傅里叶变换成像确定目标散射中心的支撑区域,然后在支撑区域内对散射中心的GTD参数进行估计,最后利用聚类方法和最小二乘方法对估计结果进行修正。仿真和暗室测量数据实验结果表明,与现有方法相比,所提方法能有效改善模型参数的估计性能,且对提高散射中心类型参数的估计精度更为明显。
文摘研究了窄带雷达信号融合问题,提出了一种基于GTD(Geometrical Theory of Diffraction)模型的窄带雷达信号多视角多波段融合的方法。在同波段多视角融合方面,利用Lincoln实验室的方法给出模型参数的初值,再运用遗传算法对参数进行迭代寻优。而在不同波段多视角融合方面,则利用视角融合后获得的同角度不同波段窄带信号联合估计频率衰减因子。并通过仿真实验以二维条带目标为例验证了方法的有效性。
