An improved two-channel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) method based on eigen-decomposition of the covariance matrix is investigated. Based on the joint Probability Density Function...An improved two-channel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) method based on eigen-decomposition of the covariance matrix is investigated. Based on the joint Probability Density Function (PDF) of the Along-Track Interferometric (ATI) phase and the similarity between the two SAR complex images, a novel ellipse detector is presented and is applied to the indication of ground moving targets. We derive its statistics and analyze the performance of detection process in detail. Compared with the approach using the ATI phase, the ellipse detector has a better performance of detection in homogenous clutter. Numerical experiments on simulated data are presented to validate the improved performance of the ellipse detector with respect to the ATI phase approach. Finally, the detection capability of the proposed method is demonstrated by measured SAR data.展开更多
In this paper,we consider the limiting spectral distribution of the information-plus-noise type sample covariance matrices Cn=1/N（Rn＋σXn）（Rn＋σXn）,under the assumption that the entries of Xn are independent but...In this paper,we consider the limiting spectral distribution of the information-plus-noise type sample covariance matrices Cn=1/N（Rn＋σXn）（Rn＋σXn）,under the assumption that the entries of Xn are independent but non-identically distributed random variables.It is proved that,almost surely,the empirical spectral distribution of Cn converges weakly to a non-random distribution whose Stieltjes transform satisfies a certain equation.Our result extends the previous one with the entries of Xn are i.i.d.random varibles to a more general case.The proof of the result mainly employs the Stein equation and the cumulant expansion formula of independent random variables.展开更多
基金Supported by the Aviation Science Fund (No. 20080152004)China Postdoctoral Foundation (No. 20090461119)
文摘An improved two-channel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) method based on eigen-decomposition of the covariance matrix is investigated. Based on the joint Probability Density Function (PDF) of the Along-Track Interferometric (ATI) phase and the similarity between the two SAR complex images, a novel ellipse detector is presented and is applied to the indication of ground moving targets. We derive its statistics and analyze the performance of detection process in detail. Compared with the approach using the ATI phase, the ellipse detector has a better performance of detection in homogenous clutter. Numerical experiments on simulated data are presented to validate the improved performance of the ellipse detector with respect to the ATI phase approach. Finally, the detection capability of the proposed method is demonstrated by measured SAR data.
基金supported by the National Natural Science Foundation of China(11071213,11101362)Natural Science Foundation of Zhejiang Province(R6090034)Specialized Research Foundation for the Doctor Program of Higher Education(20100101110001)
文摘In this paper,we consider the limiting spectral distribution of the information-plus-noise type sample covariance matrices Cn=1/N（Rn＋σXn）（Rn＋σXn）,under the assumption that the entries of Xn are independent but non-identically distributed random variables.It is proved that,almost surely,the empirical spectral distribution of Cn converges weakly to a non-random distribution whose Stieltjes transform satisfies a certain equation.Our result extends the previous one with the entries of Xn are i.i.d.random varibles to a more general case.The proof of the result mainly employs the Stein equation and the cumulant expansion formula of independent random variables.
文摘核数据不确定性是造成反应堆物理计算结果不确定性的重要因素之一。基于所需抽样核数据的协方差矩阵开发了随机抽样模块(Stochastic Sampling,SAMP),在此基础上利用SCALE(Standardized Computer Analyses for Licensing Evaluation)软件包实现了混合法和随机抽样法两种不确定性分析方法,以研究多群核数据不确定性对堆芯物理计算的影响。以3×3假想堆芯为对象,对两种方法进行了验证,然后应用于国际原子能机构(International Atomic Energy Agency,IAEA)燃料管理基准题中的Almaraz核电厂首循环堆芯。分析结果表明,两种方法结果符合良好,Almaraz核电厂堆芯keff不确定性约为0.5%,堆芯径向和轴向功率的最大不确定性分别为1.9%和0.45%。
基金The National Natural Science Foundation of China(Grant No.61102089)the Scientific Research Fund of Hunan Provincial Education Department(Grant No.11C1058)the New Courses Project of Jishou University(Grant No.2011KCB03)
