Backtracking genetic iterative reconstruction method in compressed sensing

The invention discloses a backtracking genetic iterative reconstruction method in compressed sensing. The backtracking genetic iterative reconstruction method comprises the following steps of firstly, initializing a support set of a sparse signal to be solved, carrying out cyclic iterative approximation on optimal position information of the solved sparse signal through genetic operation, such as copying, multipoint crossing, selection and big mutation treatment, carrying out backtracking updating of the support set, and lastly, projecting by utilizing a least square method to obtain amplitude information of each nonzero element of the sparse signal to be solved so as to complete signal reconstruction. According to the backtracking genetic iterative reconstruction method in compressed sensing, the sparse signal to be solved can be precisely reconstructed under the condition of unknown sparseness.