一种基于块稀疏的1比特压缩感知重构算法

块稀疏信号作为一种典型的稀疏信号,在压缩感知重构算法中被广泛应用研究,但是普通的重构算法并不能挖掘其内部结构,这导致重构精度得不到提高。在此基础上,针对普通的1比特压缩感知重构算法在块稀疏信号的重构中不能表现出良好的重构性能的问题,提出了一种专门针对块稀疏信号的1比特压缩感知重构算法。该算法以每一个块为重构单元,在二进制迭代硬阈值算法模型下进行重构。实验数据表明,提出的BLOCK-BIHT算法的重构精度比BIHT算法提高了3dB。

1 Bit Compressed Sensing Reconstruction Algorithm Based on Block Sparse

As a typical sparse signal,block sparse signal is widely used in compressed sensing reconstruction algorithm.But ordinary reconstruction algorithm cannot find its internal structure,which leads to the reconstruction accuracy decrease.Based on this theory,considering ordinary 1 bit compressed sensing reconstruction algorithm cannot have good performance in a block sparse signal,we proposed a specific reconstruction algorithm to solve block signal reconstruction.In this algorithm,each block is a reconstruction unit,and is executed reconstruction in binary iterative hard thresho-lding algorithm model.The numerical experiments show that compared with the BIHT algorithm,the precision of BLOCK-BIHT algorithm increases by 3dB.