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Saad  proposes to construct an incomplete LQ factorization of a general sparse matrix. The idea is to orthogonalize the rows of the matrix by a Gram-Schmidt process (note that in sparse matrices, most rows are typically orthogonal already, so that standard Gram-Schmidt may be not so bad as in general). Saad suggest dropping strategies for the fill-in produced in the orthogonalization process. It turns out that the resulting incomplete L factor can be viewed as the incomplete Choleski factor of the matrix . Experiments show that using in a CG process for the normal equations: is effective for some relevant problems.