Some studies have shown that optimizing the projection matrix can improve the reconstruction of compressed sensing and the sparsity range of signal adaption. This method uses iterative updated Gram matrix to maximum the optimization of compressed sensing(CS) projection matrix. It is a new method for enhancing the CS performance, which is different from previous design problems of projection matrix. Here,it analyzes, summarizes and compares the structure of those existing optimization methods of projection matrix, the application characteristics as well as existing problems, and concludes with the discussion of its possible direction of future development. The experimental results are used to verify the analysis of the conclusions.