针对现有的波达方向(direction of arrival,DOA)估计方法在低信噪比、小快拍、多信源条件下估计精度较低的问题,提出一种基于并行坐标下降算法的DOA估计方法.首先,对空域等角度均匀划分,构造超完备冗余字典;其次,采用并行坐标下降算法...针对现有的波达方向(direction of arrival,DOA)估计方法在低信噪比、小快拍、多信源条件下估计精度较低的问题,提出一种基于并行坐标下降算法的DOA估计方法.首先,对空域等角度均匀划分,构造超完备冗余字典;其次,采用并行坐标下降算法的思想对稀疏信号进行重构,得到信号在空域的稀疏系数矩阵;最后,将稀疏矩阵行向量的l2-范数映射到空域网格上,得到准确的DOA估计值.仿真实验结果表明:在低信噪比、小快拍、多信源条件下,该方法优于子空间类算法、贪婪类算法以及凸优化类算法,具有更低的均方根误差(RMSE)、更高的DOA估计精度和运行效率.展开更多
Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method ba...Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method based on edge features was proposed.Firstly,image edge gradient operator was introduced as a threshold based on the rule that the maximum value of the image edge gradient will decrease after the blurring process,making the blurred image be divided into two channels:edge channel and non-edge channel.Secondly,a double-channel loop iteration network was designed,where the edge gradient was used in the edge channel to sample the main edge structure and bilateral filtering was used in the non-edge channel to extract the detailed texture feature information.Finally,the feature information extracted from two channels was cyclically iterated to obtain a clear image using the deblurring model with maximum a posteriori probability.The experimental results showed that the image evaluation indexes obtained by the proposed deblurring model were superior to those of other algorithms,and the edge structure and texture details of the image were effectively recovered with better performance.展开更多
文摘针对现有的波达方向(direction of arrival,DOA)估计方法在低信噪比、小快拍、多信源条件下估计精度较低的问题,提出一种基于并行坐标下降算法的DOA估计方法.首先,对空域等角度均匀划分,构造超完备冗余字典;其次,采用并行坐标下降算法的思想对稀疏信号进行重构,得到信号在空域的稀疏系数矩阵;最后,将稀疏矩阵行向量的l2-范数映射到空域网格上,得到准确的DOA估计值.仿真实验结果表明:在低信噪比、小快拍、多信源条件下,该方法优于子空间类算法、贪婪类算法以及凸优化类算法,具有更低的均方根误差(RMSE)、更高的DOA估计精度和运行效率.
基金supported in part by Natural Science Research Foundation of Shanxi Province(Nos.20210302123019,20210302124195,20210302124212,20210302123189)。
文摘Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method based on edge features was proposed.Firstly,image edge gradient operator was introduced as a threshold based on the rule that the maximum value of the image edge gradient will decrease after the blurring process,making the blurred image be divided into two channels:edge channel and non-edge channel.Secondly,a double-channel loop iteration network was designed,where the edge gradient was used in the edge channel to sample the main edge structure and bilateral filtering was used in the non-edge channel to extract the detailed texture feature information.Finally,the feature information extracted from two channels was cyclically iterated to obtain a clear image using the deblurring model with maximum a posteriori probability.The experimental results showed that the image evaluation indexes obtained by the proposed deblurring model were superior to those of other algorithms,and the edge structure and texture details of the image were effectively recovered with better performance.
