Abstract: A novel spreading sequence estimation based on autocorrelation-like matrix for (CCSK) signals is proposed. The estimation problem is represented as the minimization of norm 0 for the autocorrelation-like matrix, which is also equivalent to the one of rank-1 approximation in the sense of norm 0. A non-iterative algorithm is proposed for the optimization problem, which exploits whole autocorrelation-like matrix to correct wrong elements of the matrix by noise. Based on the estimated symbol bits, the received symbol waveforms are circle-shifted so that they have the same phase, and then these circle-shifted symbol waveforms are averaged to obtain the estimation of the spreading sequence. Simulations results show proposed method has significant performance improvement than traditional method, and it is effective especially under low signal-noise-rate (SNR) scenarios.