The invention discloses an effective '0,1' sparse signal compressed sensing reconstruction method. The method mainly comprises a sparse and uniform measurement matrix construction part and an iteration reconstruction order part based on a bipartite graph. According to the method, a bipartite graph model in a graph theory is ingeniously introduced, the minimum cover characteristic of the bipartite graph is closely combined, a constraint condition is appropriately added, and the sparse, uniform and minimally-covered measurement matrix is constructed. Based on the special structure that the '0,1' sparse signals are fully utilized in an iteration reconstruction algorithm based on the bipartite, the connecting line phi ij of the bipartite graph is deleted and a measurement value y is updated through an iteration method, and an original signal reconstruction method is achieved finally. According to the method, the bipartite graph model in the graph theory is introduced in compressed sensing sampling and reconstruction, compared with an l1 norm minimization method, reconstruction errors do not exist, the method can be applied to compressive sampling of neutron pulse sequences, earthquake signals, wireless sensor networks, binary images and the like.