The performance of the existing spectrum sensing algorithms based on goodness of fit (GoF) tests are excellent, however, they are sensitive to the noise uncertainty. In this paper, the first component of Cramer-von Mises, insensitive to variances shift, is employed as test statistic in GoF test and a fast spectrum sensing based on the component of Cramervon Mises is proposed. The detection probability and false alarm probability of the proposed method are analyzed, and its theoretical threshold is derived. Simulation results demonstrate that the proposed method can overcome the noise uncertainty and has lower complexity compared with Cramer-Von Mises (CM) criterion, and the false alarm probability can satisfy the requirements of the standard. © 2018 IEEE.