The pseudo-random noise (PRN) code modulated in satellite navigation signals impacts the system positioning performance directly, and the code monitoring is one of the key technologies. However, the received signal is often buried in noise, and the ranging codes can not visible in time domain. Considering local clock bias, the signal model in transmission link is derived in this paper, and a PRN code blind-decoding method is proposed also. It calculates the signal’s cyclic spectrum by using fast Fourier transform accumulation method (FAM), and estimates the code rate and Doppler frequency making use of the noise eliminating characteristic in non-zero cycle frequency cross-section. Wiped off the Doppler shift, the navigation message or secondary code bits are determined and removed by slide-correlating a small slice of itself with the whole data. The start of the code is determined by stacking multiple periods of the whole data into a code period, and then the whole data is shifted to the start of the PRN code, and is restacked. Then the individual period of PRN code is estimated. An experiment for the proposed algorithm is performed by simulated vector signal analyzer (VSA) collected data. The results indicate that the algorithm is effective and reliable. The pseudo-random noise (PRN) code modulated in satellite navigation signals impacts the system positioning performance directly, and the code monitoring is one of the key technologies. However, the received signal is often buried in noise, and the ranging codes can not be visible Considering local clock bias, the signal model in transmission link is derived in this paper, and a PRN code blind-decoding method is proposed also. It calculates the signal’s cyclic spectrum by using fast Fourier transform accumulation method (FAM), and estimates the code rate and Doppler frequency making use of the noise eliminating characteristic in non-zero cycle frequency cross-section. Wiped off the Doppler shift, the navigation message or secondary code bits are determined and removed by slide-correlating a small slice of itself with the whole data. The start of the code is determined by stacking multiple periods of the whole data into a code period, and then the whole data is shifted to The start of the PRN code, and is restacked. Then the individual period of PRN code is estimated. An experiment for the proposed algorithm is performed by simulated vector signal analyzer (VSA) collected data. The results indicate that the algorithm is effective and reliable .