ID 原文 译文
21615 该文使用香港轻轨系统数据集以及公开测试数据集进行方法测试。 Practical field tests are done on real data of the light railway system in Hong Kong and the open test data set in Nordland.
21616 实验结果表明，该文方法在实现快速匹配的同时，其匹配正确率较基于全局特征匹配方法SeqSLAM提高了9.8%。 The experimental results show that the proposed method achieves fast matching and the precision is 9.8% higher than SeqSLAM which is based on global feature.
21617 针对双基地MIMO雷达收发角及多普勒联合频率估计问题，该文基于参数流型矩阵的多维范德蒙德结构特征，提出一种低运算量的3维参数联合估计算法。 In order to solve the problem of Direction Of Departure (DOD), Direction Of Arrival (DOA) and Doppler frequency estimation in bistatic MIMO radar, a low complexity method is proposed for joint estimationof the three parameters based on the multi-dimensional Vandermonde structure characteristic of the parameter manifold matrices.
21618 首先根据回波模型的多维结构特性构造3阶张量，并对其分别沿发射维、接收维和脉冲维切片得到3个等效矩阵； First, a third-order tensor is constructed according to the multi-dimensional structure of the echo model. Three equivalent matrices are obtained by cutting the tensor along transmit dimension, receive dimension and pulse dimension respectively.
21619 然后结合多维范德蒙德结构特征和等效矩阵的左奇异矩阵具有Khatri-Rao乘积结构特征，估计收发阵列流型矩阵和多普勒流型矩阵； Then, combining the multi-dimensional Vandermonde characteristic with the Khatri-Rao product characteristic of the left-singular matrix of the equivalent matrix, transmit manifold matrix, receive manifold matrix and Doppler manifold matrix are estimated.
21620 最后通过Root-MUSIC算法估计收发角和多普勒频率。 Finally, theDOD, DOA and Doppler frequency are estimated by Root-MUSIC algorithm.
21621 与现有算法相比，该算法显著改善了参数估计精度，在小脉冲数下，其运算量与旋转不变子空间算法(ESPRIT)相当。 Compared with the existing methods, the proposed algorithm improves obviously the estimation precision, and its computational cost is comparable to that of Estimation of Signal Parameters via Rotation Invariant Techniques (ESPRIT) method in small pulse number.
21622 仿真实验验证了该算法的有效性。 The effectiveness of the proposed method is verified by simulation results.
21623 用户分组算法作为非正交多址接入(NOMA)的关键部分，对系统吞吐量和用户公平性具有重要影响。 As a key part in Non-Orthogonal Multiple Access (NOMA), user grouping is of particular importance for non-orthogonal multiple access system to improve throughput performance and user fairness.
21624 当用户数量和可用的资源增加时，用户分组的最佳调度将变得不可行，该文提出一种子带间多用户分组优化算法。 When the number of users and the available resources is increased, the optimal scheduling of user grouping will be infeasible, so a multi-user grouping optimization algorithm for different sub-bands is proposed.