ID 原文 译文
53537 双站结构参数及双站扭曲项的距离向空变性用回波数据的距离向分块处理，推导了数据分块条件，由此可以实现宽场景成像。 The variance of bistatic parameters and bistatic deformation in range can be compensated by data blocking in range, so the algorithm can be easily expanded to wide scene focusing.
53538 算法基于更精确的 ELBF，并用 CS 方法校正点目标距离徙动，处理流程更简单，成像效率更高， With more accurate 2-D frequency spectrum formula and good range cell migration correction (RCMC) method, the processing procedure of algorithm is simplified and imaging efficiency is also improved.
53539 仿真验证了本文算法处理并行机载双站斜视 SAR数据的有效性。 Simulations validate the proposed algorithm to process the parallel airborne bistatic squint SAR data
53540 以最大化规范四阶累积量绝对值为目标函数，解决了因概率密度函数估计过程中激活函数选取不当而带来算法分离性能下降的问题; Considering maximizing the absolute value of normalized fourth-order cumulant as the objective function can avoid decline of algorithm performance caused by unsuitable activation function which is used to estimate probability density function.
53541 引入 PSO-CF 方法进行优化问题求解，防止算法收敛到局部极值，降低算法的实现复杂度。 For solving the optimization problem, particle swarm optimization with constriction factor is chosen to prevent algorithm from converging at local extremum, and then reduce the algorithm complexity of achievement.
53542 为高效实现从多源混合信号中抽取有限数目的目标信号，提出了一种基于 PSO-CF 的有限目标信号盲抽取算法。 A limited blind target signal extract algorithm based on PSO-CF is proposed in order to extract limited blind target signals from all source signals.
53543 仿真表明，该算法对超高斯、亚高斯及混合型源信号均可分离，算法普适性强，且收敛速度快，分离性能良好。 Simulation shows that super-Gaussian, sub-Gaussian or mixed source signals can be successfully separated by the algorithm, which has a good applicability, fast convergence speed and great separation performance.
53544 论文提出了一种基于特征向量稀疏分解的 DOA 估计方法。 The thesis proposes a novel DOA (direction of arrival) estimation method using sparse decomposition of eigenvector on the basic of the sparse characteristic of space signals.
53545 依据阵列协方差矩阵的最大特征向量是所有信号导向矢量的线性组合这一性质。 Firstly, the biggest eigenvector of covariance matrix is proved to be the linear combination of all steer vectors.
53546 利用阵列协方差矩阵的最大特征向量建立稀疏模型进行 DOA 估计。该方法能有效降低噪声的影响，避免估计信号源数目，增强了算法的鲁棒性。 Then the biggest eigenvector of covariance matrix is extracted to build sparse decomposition model for DOA estimation, the effects caused by the noise is largely reduced and the sources number estimation is able to skip by this method.