ID 原文 译文
18895 相比于单一的1维Logistic映射的混沌系统，基于Logistic映射与Sine映射的复合离散混沌系统具有更大的密钥空间。 Moreover, it has larger secret key space compared with the single one-dimensional Logistic mapping chaotic system.
18896 该文运用Lyapunov指数与NIST测试验证了该混沌系统的混沌特性及随机性，并仿真验证了双重加密方案的保密性能。 The performance of doubleencryption is measured by verifying its chaotic characteristics and randomness (Lyapunov exponent and NIST)as well as its security performance in simulation.
18897 仿真结果表明，该文所提出的加密方案密钥空间为4×1093，Lyapunov指数提高到0.9850，NIST测试中最大P值为0.9995。 The results show that Lyapunov index is increased to 0.9850,and the maximum P-value in the NIST test is 0.9995 by using the proposed double encryption in this paper.
18898 该双重加密方案可在不影响传输性能下极大提升OFDM通信系统的安全性。 It indicates such double encryption significantly improve the confidentiality of the OFDM communication system without affecting the transmission performance.
18899 该文针对有限次采样导致传统波达方向角(DOA)估计算法存在较大估计误差的问题，提出一种基于稀疏低秩分解(SLRD)的稳健DOA估计方法。 Focusing on the problem of rather large estimation error in the traditional Direction Of Arrival(DOA) estimation algorithm induced by finite subsampling, a robust DOA estimation method based onSparseand Low Rank Decomposition (SLRD) is proposed in this paper.
18900 首先，基于低秩矩阵分解方法，将接收信号协方差矩阵建模为低秩无噪协方差及稀疏噪声协方差矩阵之和； Following the low-rank matrixde composition method, the received signal covariance matrix is firstly modeled as the sum of the low-rank noise-free covariance matrix and sparse noise covariance one.
18901 而后基于低秩恢复理论，构造关于信号和噪声协方差矩阵的凸优化问题； After that, the convex optimization problem associated with the signal and noise covariance matrix is constructed on the basis of the low rank recovery theory.
18902 再者构建关于采样协方差矩阵估计误差的凸模型，并将此凸集显式包含进凸优化问题以改善信号协方差矩阵估计性能进而提高DOA估计精度及稳健性； Subsequently, a convex model of the estimation error of the sampling covariance matrix can be formulated, and this convex set is explicitly included into the convex optimization problem to improve the estimation performance of signal covariance matrix such that the estimation accuracy and robustness of DOA can be enhanced.
18903 最后基于所得最优无噪声协方差矩阵，利用最小方差无畸变响应(MVDR)方法实现DOA估计。 Finally, with the obtained optimal noiseless covariance matrix, the DOA estimation can be implemented by employing the Minimum Variance Distortionless Response (MVDR) method.
18904 此外，基于采样协方差矩阵估计误差服从渐进正态分布的统计特性，该文推导了一种误差参数因子选取准则以较好重构无噪声协方差矩阵。 In addition, exploiting the statistical characteristics of the sampling covariance matrix estimation error subjecting to the asymptotic normal distribution, an error parameter factor selection criterion is deduced to reconstruct the noise-free covariance matrix preferably.