ID 原文 译文
48306 利用参考样本估计海杂波的协方差矩阵,最典型的方法是归一化样本协方差矩阵(normalized sample covariance matrix,NSCM),它隐含着假设参考样本的散斑分量具有相同的统计特性。 The reference sample is used to estimate the sea clutter covariance matrix, the most typical method is to normalized sample covariance matrix (normalized sample covariance matrix, NSCM), it implied assumption of reference sample speckle component with the same statistical properties.
48307 这一假设成立与否取决于海杂波是否具有空间均匀性。 This hypothesis was established or not depends on whether the sea clutter has spatial uniformity.
48308 为了摆脱NSCM对散斑分量的假设,提出了一种基于对角加载的协方差矩阵估计算法(NSCM-L),该算法自适应组合NSCM和单位矩阵,其组合系数随着参考样本的统计特性变化而自适应地变化。 In order to get rid of NSCM hypothesis of speckle component, presents a covariance matrix estimation algorithm based on diagonal loading (NSCM - L), the algorithm of adaptive combination NSCM and unit matrix, the combination coefficient with the change of the statistical features of the reference sample and adaptive to change.
48309 利用广义似然比检测器(generalized likelihood ratio detector,GLRT)检测实测海杂波中的扩展目标,实验结果表明,当分辨率为3m时,NSCM-L性能改善高达15dB。 Using the generalized likelihood ratio detector (generalized likelihood thewire detector, GLRT) to detect the observed sea clutter of extended target, the experimental results show that when the resolution is 3 m, NSCM - L up to 15 db performance improvement.
48310 对于非线性系统的直接加权优化辨识算法,通过在原线性仿射函数形式中,增加若干关于输入观测数据序列的线性项来增强逼近非线性。 The direct weighted optimization identification algorithm for nonlinear systems, through in the form of the original linear affine function, increase the number of input data sequence of linear to enhance approximation nonlinear.
48311 对于增加若干线性项后展开式中的两类未知权重值的选取,分别从理论和实用上推导出这些未知权重值的选取过程,并明确权重值间的关键和辅助作用。 Item to increase the number of linear expansion after the selection of two classes of unknown weights, respectively from the theoretical and practical selection process of the unknown weight value is deduced, and clearly weights between the key and the auxiliary function.
48312 理论上的推导分析可明确增加的未知权重值在整个逼近非线性系统的目的中起着辅助作用; Theoretical analysis can be clearly increased the unknown weight value is derived in the approximation of nonlinear system plays a supplementary role;
48313 实用上的推导分析展示了怎样将某些复杂的最优化问题经过整理变换成常见的最优化问题, the purpose ofDerivation on the practical analysis shows how some complex optimization problems through sorting into common optimization problem,
48314 从而可利用最基础的优化方法来求解,并分别对理论和实用算法的收敛性做了必要的证明。 which can use the most basic optimization method to solve, and the convergence of theoretical and practical algorithm respectively do the necessary proof.
48315 最后用仿真算例验证所提方法的有效性和可行性。 In the end, the simulation examples verify the feasibility and effectiveness of the proposed method.