基金supported by the Chinese Ministry of Education of Humanities and Social Science Project (23YJC72040003)the Key Project of Chinese Ministry of Education (22JJD720021)+2 种基金the Young Scholars Program of Shandong University (11090089964225)the International Scientific Cooperation Seed Fund of Shandong University (11090089395416)supported by the Taishan Young Scholars Program of the Government of Shandong Province,China (No.tsqn201909151)。
文摘调制宽带转换器(modulated wideband converter,MWC)采样方法针对稀疏宽带信号实现了可精确重构的亚奈奎斯特采样,缓解了采样率高的压力。然而现有重构算法所需的最小通道数和采样率与理论下限值仍存在较大差距。针对该问题基于奇异值分解(singular value decomposition,SVD)和多信号分类(multiple signal classification,MUSIC)思想提出一种间接重构算法。该算法首先利用SVD思想通过降维变换在不改变未知矩阵支撑集的前提下将MWC采样模型转化为低维的多测量向量(multiple measurement vector,MMV)问题,然后利用MUSIC思想获取支撑集,最后通过伪逆实现重构。实验结果表明,与传统重构算法相比,该算法可以进一步降低采样率要求,在较少的通道数下实现高概率重构,在一定条件下,重构所需的最低通道数已接近理论下限值。