基于高阶奇异值分解(High Order Singular Value Decomposition,HOSVD)降噪的信道预测算法对天线数较少引起的秩不足问题比较敏感,同时也难以应付较大多普勒频移的情况,从而引起信道估计性能和预测性能的急剧下降、损失信道容量.针对这...基于高阶奇异值分解(High Order Singular Value Decomposition,HOSVD)降噪的信道预测算法对天线数较少引起的秩不足问题比较敏感,同时也难以应付较大多普勒频移的情况,从而引起信道估计性能和预测性能的急剧下降、损失信道容量.针对这一问题,提出了一种改进的使用HOSVD降噪的信道预测算法.该算法先利用多输入多输出(Multiple-input Multiple-Output,MIMO)信道固有的空时相关性对采样得到的信道状态信息(Channel State Information,CSI)进行矩阵重排和数据平滑处理,随后基于信道的多维结构特性,使用HOSVD降低噪声的影响,继而重构信道矩阵,最后利用递归最小二乘滤波器对未来时刻的信道状态进行预测.仿真表明,所提算法的估计误差和预测误差性能均明显优于对比算法,这是因为所提算法通过矩阵重排和空时平滑,虚拟地增加了天线数,降低了秩缺失问题对估计和预测精度的影响,从而有效补偿了因误差所致的信道容量的损失.同时,对比天线数和多普勒频移对不同算法性能的影响可见,所提算法也能在大多普勒频移和天线数较少等不利条件下提供较好预测性能和信道容量,具有一定的优越性.展开更多
This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（H...This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（HOSVD） approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product（TP） model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities（LMIs） constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach.展开更多
针对短相干积累时间(coherent integration time,CIT)引起的多普勒分辨率低,无法从强大海杂波中检测出舰船目标的问题,提出了基于高阶奇异值分解(higher order singular value decomposition,HOSVD)的海杂波抑制算法。首先利用相邻单元...针对短相干积累时间(coherent integration time,CIT)引起的多普勒分辨率低,无法从强大海杂波中检测出舰船目标的问题,提出了基于高阶奇异值分解(higher order singular value decomposition,HOSVD)的海杂波抑制算法。首先利用相邻单元内海杂波的相干性,将毗邻距离单元和方位单元的多脉冲接收数据应用三阶张量表示,然后采用HOSVD方法求解三阶张量的海杂波子空间和目标子空间的投影矩阵,最后利用投影矩阵将三阶张量映射到目标子空间以抑制海杂波。该方法与现有子空间类海杂波抑制方法相比,提高了信干噪比(signal to clutter plus noise ratio,SCNR)和峰值旁瓣电平比(peak sidelobe level ratio,PSLR),解决了目标谱峰偏移问题。展开更多
文摘基于高阶奇异值分解(High Order Singular Value Decomposition,HOSVD)降噪的信道预测算法对天线数较少引起的秩不足问题比较敏感,同时也难以应付较大多普勒频移的情况,从而引起信道估计性能和预测性能的急剧下降、损失信道容量.针对这一问题,提出了一种改进的使用HOSVD降噪的信道预测算法.该算法先利用多输入多输出(Multiple-input Multiple-Output,MIMO)信道固有的空时相关性对采样得到的信道状态信息(Channel State Information,CSI)进行矩阵重排和数据平滑处理,随后基于信道的多维结构特性,使用HOSVD降低噪声的影响,继而重构信道矩阵,最后利用递归最小二乘滤波器对未来时刻的信道状态进行预测.仿真表明,所提算法的估计误差和预测误差性能均明显优于对比算法,这是因为所提算法通过矩阵重排和空时平滑,虚拟地增加了天线数,降低了秩缺失问题对估计和预测精度的影响,从而有效补偿了因误差所致的信道容量的损失.同时,对比天线数和多普勒频移对不同算法性能的影响可见,所提算法也能在大多普勒频移和天线数较少等不利条件下提供较好预测性能和信道容量,具有一定的优越性.
基金supported by the National Natural Science Foundation of China(6120300761304239+1 种基金61503392)the Natural Science Foundation of Shaanxi Province(2015JQ6213)
文摘This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（HOSVD） approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product（TP） model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities（LMIs） constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach.
文摘针对短相干积累时间(coherent integration time,CIT)引起的多普勒分辨率低,无法从强大海杂波中检测出舰船目标的问题,提出了基于高阶奇异值分解(higher order singular value decomposition,HOSVD)的海杂波抑制算法。首先利用相邻单元内海杂波的相干性,将毗邻距离单元和方位单元的多脉冲接收数据应用三阶张量表示,然后采用HOSVD方法求解三阶张量的海杂波子空间和目标子空间的投影矩阵,最后利用投影矩阵将三阶张量映射到目标子空间以抑制海杂波。该方法与现有子空间类海杂波抑制方法相比,提高了信干噪比(signal to clutter plus noise ratio,SCNR)和峰值旁瓣电平比(peak sidelobe level ratio,PSLR),解决了目标谱峰偏移问题。
基金国家重点基础研究发展计划项目(973计划)(2014CB-239506)国家电网公司科技项目(52020114026L)+1 种基金Project Supported by the National Basic Research Program(973 Program)(2014CB239506)Science and Technology Project of State Grid Corporation of China(52020114026L)
