ID	原文	译文
53777	针对分布式多输入多输出(Multiple-input Multiple-output，MIMO)雷达回波信号相参积累问题，提出了一种利用信息熵作为优化准则的多节点回波相位补偿与相参积累方法。	The coherent accumulation problem of distributed multiple-input multiple-output(MIMO) radar was studied. We proposed a phase compensation and coherent accumulation algorithm of multi-node echoes, which used information entropy as an optimization criterion.
53778	采用正交频分复用线性调频信号(Orthogonal Frequency Division Multiplexing Linear Frequency Modulated Signal，OFDM-LFM)作为发射波形，通过匹配滤波完成耦合回波分离和脉冲压缩，然后在频域进行频移操作消除步进频的相位影响，利用信息熵估计距离对齐后的多节点回波相位差，随后构建相应的相位补偿函数，进而完成各节点回波的相位差异补偿，最终得到分布式MIMO雷达多节点回波信号的相参积累结果。	Orthogonal frequency division multiplexing linear frequency modulated(OFDM-LFM) signal was used as emission waveforms. The signal separation of coupling echoes and pulse compression were completed by matched filtering. In order to eliminate the impact of step frequency, we took frequency shift operation in the frequency domain. Information entropy function of the range alignment echoes was used to estimate the phase parameters, then we constructed the phase compensated function to compensate the phase differences of multi-node echoes. Finally, We obtained the coherent accumulation result of distributed MIMO radar.
53779	所提方法可同时处理多个节点回波，仿真实验验证了该方法的有效性。	The proposed method can deal with the echoes of multiple nodes at the same time, simulation results are provided to verity the validity of the proposed method.
53780	矩阵低秩估计模型在图像处理任务中有着广泛地运用。	Low-rank matrix approximation models have been successfully applied to numerous vision tasks.
53781	针对图像去模糊，利用矩阵低秩先验能保留图像的重要边缘信息从而实现去模糊。	For image deblurring, the use of low-rank prior can retain the important edge information.
53782	而对于多帧图像去模糊，基于矩阵的低秩模型并未充分考虑多帧图像间的时序和空间关系。	However, for multi-frame image deblurring, the low-rank matrix models do not consider the temporal and spatial relationship among multi-frame images.
53783	针对该问题，我们提出基于三维张量低秩先验的多帧视频图像盲去模糊模型。在模型中，首先将多帧连续图像按时序维堆叠成张量，显式地考虑多帧图像间的时空关系，同时利用张量低秩先验约束保留图像重要纹理结构信息。	In this paper, we propose a low-rank prior deblurring model based on a three-dimensional tensor, we pile up the continuous images into a tensor according to the temporal dimension, and use the tensor low-rank prior constraint, which not only maintains the dominant texture structure information to estimate the blur kernel but also considers the spatiotemporal relationship among multiple frames.
53784	利用交替迭代的方法求解模型，实现去模糊。	We solve the energy model by alternating direction minimization method.
53785	通过在不同的数据集上实验结果表明，该方法能达到较好的去模糊结果。	The experimental results on different datasets show that our method can achieve better results.
53786	在空中交通监视系统中使用的现代技术中，广播式自动相关监视(ADS-B)是当今最引人注目的一种，它具有更高的准确性和更少的人为依赖。	Among the modern technologies used in air traffic surveillance systems, Automatic Dependent Surveillance-Broadcast(ADS-B) is the most eye-catching one today, with higher accuracy and less human dependence.