ID	原文	译文
54057	相干目标的波达方向估计一直是雷达信号处理中的一个难题。	The direction of arrival(DOA) estimation of coherent targets has always been a difficult problem in the field of radar signal processing.
54058	为了获得更好的相干信号角度估计精度，并提高算法可实现性，在多输入、多输出雷达的基础上，提出一种极化平滑降维酉旋转不变性参数估计算法。	In order to obtain better angle estimation accuracy for coherent signals and improve the achievability of the algorithm, a polarization smoothing and dimensionality reduction unitary estimation of signal parameters via rotational invariance(ESPRIT) technique is proposed on the basis of multi-input and multi-output radar.
54059	首先通过降维矩阵对接收信号数据进行降维处理，然后利用降维后的接收数据构造中心复共轭对称矩阵，再构建适当的酉矩阵对其进行实值处理，然后对其进行极化平滑解相干处理，最后构造出实值旋转不变性方程估计目标的波达方向。	First, reduce the dimension of the received signal data through the dimension reduction matrix, then use the reduced dimension to construct the central complex conjugate symmetric matrix, and then construct an appropriate unitary matrix to perform real-value processing, and then polarize and smooth it Solve the coherent processing, and finally construct a real-value rotation invariance equation to estimate the direction of arrival of the target.
54060	相比于常规的极化平滑旋转不变性参数估计算法，本文所提极化平滑降维酉旋转不变性参数估计算法的相干信号角度估计精度更高、更利于工程实现。	Compared with the conventional polarization smoothing rotation invariance parameter estimation algorithm, the polarization smoothing dimensionality reduction unitary rotation invariance parameter estimation algorithm proposed in this paper not only has higher coherent signal angle estimation accuracy and lower robustness, but also has Lower the amount of calculation and more conducive to engineering realization.
54061	第5节通过仿真实验证明了该算法的有效性与真实性。	The fifth section uses MATLAB software to simulate the proposed algorithm and the comparison algorithm. The simulation experiment proves the validity and authenticity of the algorithm.
54062	为了提高盲源分离(blind source separation，BSS)算法在混响和噪声环境下的鲁棒性，提出了一种适用于欠定情况下用于卷积混合信号的盲源分离算法。	To improve the robustness of the blind source separation algorithm in the presence of reverberation and noise, a blind source separation method for convolutional mixed signals under underdetermined conditions is proposed in this work.
54063	在该算法中，利用高混响环境下混合模型即使在时频(time-frequency，TF)域中仍具有卷积特性，	Due to the high reverberation, the mixing model presents convolution property even in the time-frequency(TF) domain.
54064	并结合房间冲激响应(room impulse response，RIR)的统计规律，将时频域中的瞬时模型扩展到更适合高混响环境的卷积模型，进而构建一欠定盲源分离优化问题，最后，采用交替方向乘子法(alternating direction method of multipliers，ADMM)优化框架来求解该问题。	By using the characteristics of room impulse response, the instantaneous model in the TF domain is extended to a convolution model is more suitable for high reverberation environments, Based on the convolution model in the TF domain, a joint optimization problem of blind source separation is developed, and the resulting optimization problem is solved via an alternating optimization framework where the alternating direction method of multipliers(ADMM) is devised.
54065	仿真实验结果表明，在混响环境下，本文提出的基于卷积模型的盲源分离算法与现有盲源分离算法相比，具有非常明显的性能优势。	The results of simulation experiments show that the performance of the convolution model in the reverberation environment outperforms the instantaneous model, which verifies the effectiveness of the convolution model in the TF domain.
54066	针对传统的变换域通信系统多址干扰严重，抑制用户数和误码率性能的问题，提出了一种分区方法降低多址干扰，适用于大规模变换域多址通信。	In view of the serious multi-access interference in traditional transform domain communication systems(TDCS), which can suppress the performance of users and bit error rate, a partition multi-access interference reduction method is proposed, which is suitable for large-scale transform domain multi-access communication.