针对分布式多输入多输出(multi-input multi-output,MIMO)雷达测向中存在的数据信息提取不充分、运算量偏大等问题,开展了基于广义奇异值分解(generalized singular value decomposition,GSVD)的测向算法研究,以提高低信噪比条件下的角...针对分布式多输入多输出(multi-input multi-output,MIMO)雷达测向中存在的数据信息提取不充分、运算量偏大等问题,开展了基于广义奇异值分解(generalized singular value decomposition,GSVD)的测向算法研究,以提高低信噪比条件下的角度估计性能。首先,建立了分布式阵列MIMO雷达回波信号的统一化表征模型;其次,将分布式MIMO雷达系统接收阵列数据的多线程GSVD问题转换为一个联合优化问题,运用交替最小二乘(alternating least squares,ALS)技术实现阵列信号流行矩阵的拟合,并引入子空间类算法实现目标角度联合估计;最后,对优化问题增加l1范数约束,避免了每次迭代中进行的奇异值分解运算,降低了算法运算量。仿真实验从角度联合估计、均方误差、运算时间等方面验证了所提算法的有效性。展开更多
In this paper,the generalized inverse eigenvalue problem for the（P,Q）-conjugate matrices and the associated approximation problem are discussed by using generalized singular value decomposition（GSVD）.Moreover,the ...In this paper,the generalized inverse eigenvalue problem for the（P,Q）-conjugate matrices and the associated approximation problem are discussed by using generalized singular value decomposition（GSVD）.Moreover,the least residual problem of the above generalized inverse eigenvalue problem is studied by using the canonical correlation decomposition（CCD）.The solutions to these problems are derived.Some numerical examples are given to illustrate the main results.展开更多
This paper presents noncooperative and cooperative security transmission schemes for multiple-input multiple-output（MIMO） Gaussian wiretap channel with one helper for antenna configuration with arbitrary number. In ...This paper presents noncooperative and cooperative security transmission schemes for multiple-input multiple-output（MIMO） Gaussian wiretap channel with one helper for antenna configuration with arbitrary number. In these two schemes, the transmitter performs beamforming based on generalized singular value decomposition（GSVD）, where an appropriate power allocation algorithm is utilized. Meanwhile, the helper sends artificial noise for higher secrecy rate. However, the transmission strategies for the artificial noise are different in the two schemes. In the first scheme, the helper adopts GSVD-based beamforming. Nevertheless, in this scheme, the impact of the artificial noise on the information signal at the receiver is not considered. To solve the problem, the helper performs space projection（SP）-based beamforming in the second scheme. In this scheme, suboptimal weighting factors are introduced to reduce the computational complexity, which can be adapted to the change of the channel quality. Theoretical analysis for the performance of the two proposed schemes is then given. Furthermore, simulation results indicate that the two presented schemes perform better than the existed schemes without helper. They also show that in the second scheme the suboptimal parameter setting is better than equal parameter setting and quite close to optimal parameter setting.展开更多
在GSVD(Generalized Singular Value Decomposition)多麦克风语音去噪方法中引入子带和QR(Orthogonal-Triangular Decomposition),从而提高了矩阵的分解速度.改进的方法由于对输入信号进行抽取和正三角分解的预处理,降低了计算复杂度....在GSVD(Generalized Singular Value Decomposition)多麦克风语音去噪方法中引入子带和QR(Orthogonal-Triangular Decomposition),从而提高了矩阵的分解速度.改进的方法由于对输入信号进行抽取和正三角分解的预处理,降低了计算复杂度.实验结果表明了改进方法的有效性和可行性.展开更多
提出一种新的通用旁瓣消除器结构,它利用广义奇异值分解(Generalized singular value decomposition,GSVD)技术,通过广义奇异向量的变换间接估计声源到麦克风之间的传递函数。不同噪声环境下的实验结果表明,与现有的各种GSC算法相比,该...提出一种新的通用旁瓣消除器结构,它利用广义奇异值分解(Generalized singular value decomposition,GSVD)技术,通过广义奇异向量的变换间接估计声源到麦克风之间的传递函数。不同噪声环境下的实验结果表明,与现有的各种GSC算法相比,该算法能够更有效地抑制混响和噪声,并且增强后的语音失真最小。展开更多
文摘针对分布式多输入多输出(multi-input multi-output,MIMO)雷达测向中存在的数据信息提取不充分、运算量偏大等问题,开展了基于广义奇异值分解(generalized singular value decomposition,GSVD)的测向算法研究,以提高低信噪比条件下的角度估计性能。首先,建立了分布式阵列MIMO雷达回波信号的统一化表征模型;其次,将分布式MIMO雷达系统接收阵列数据的多线程GSVD问题转换为一个联合优化问题,运用交替最小二乘(alternating least squares,ALS)技术实现阵列信号流行矩阵的拟合,并引入子空间类算法实现目标角度联合估计;最后,对优化问题增加l1范数约束,避免了每次迭代中进行的奇异值分解运算,降低了算法运算量。仿真实验从角度联合估计、均方误差、运算时间等方面验证了所提算法的有效性。
基金Supported by the Key Discipline Construction Project of Tianshui Normal University
文摘In this paper,the generalized inverse eigenvalue problem for the（P,Q）-conjugate matrices and the associated approximation problem are discussed by using generalized singular value decomposition（GSVD）.Moreover,the least residual problem of the above generalized inverse eigenvalue problem is studied by using the canonical correlation decomposition（CCD）.The solutions to these problems are derived.Some numerical examples are given to illustrate the main results.
基金supported by the National Natural Science Foundation of China (61271259,61471076,61301123)the Research Project of Chongqing Education Commission (KJ120501,KJ120502)+1 种基金the Program for Changjiang Scholars and Innovative Research Team in University (IRT1299)the Special Fund of Chongqing Key Laboratory (CSTC)
文摘This paper presents noncooperative and cooperative security transmission schemes for multiple-input multiple-output（MIMO） Gaussian wiretap channel with one helper for antenna configuration with arbitrary number. In these two schemes, the transmitter performs beamforming based on generalized singular value decomposition（GSVD）, where an appropriate power allocation algorithm is utilized. Meanwhile, the helper sends artificial noise for higher secrecy rate. However, the transmission strategies for the artificial noise are different in the two schemes. In the first scheme, the helper adopts GSVD-based beamforming. Nevertheless, in this scheme, the impact of the artificial noise on the information signal at the receiver is not considered. To solve the problem, the helper performs space projection（SP）-based beamforming in the second scheme. In this scheme, suboptimal weighting factors are introduced to reduce the computational complexity, which can be adapted to the change of the channel quality. Theoretical analysis for the performance of the two proposed schemes is then given. Furthermore, simulation results indicate that the two presented schemes perform better than the existed schemes without helper. They also show that in the second scheme the suboptimal parameter setting is better than equal parameter setting and quite close to optimal parameter setting.
文摘在GSVD(Generalized Singular Value Decomposition)多麦克风语音去噪方法中引入子带和QR(Orthogonal-Triangular Decomposition),从而提高了矩阵的分解速度.改进的方法由于对输入信号进行抽取和正三角分解的预处理,降低了计算复杂度.实验结果表明了改进方法的有效性和可行性.
文摘提出一种新的通用旁瓣消除器结构,它利用广义奇异值分解(Generalized singular value decomposition,GSVD)技术,通过广义奇异向量的变换间接估计声源到麦克风之间的传递函数。不同噪声环境下的实验结果表明,与现有的各种GSC算法相比,该算法能够更有效地抑制混响和噪声,并且增强后的语音失真最小。
