The GNSS signal within the urban canyon areas suffers from the severe blockage and variable quality, which can lead to the inaccurate or even ineffective positioning of intelligent vehicles. To effectively utilize available satellite observations, a multi-sensor fusion method based on camera-aided GNSS / INS integration is proposed. Firstly, a sky-pointing camera is utilized to capture the sky view image and exclude the NLOS measurements, meanwhile the satellites distribution state is defined by the remaining LOS measurements with orthogonal linear regression method. Additionally a factor graph fusion framework based on GNSS / INS integration is proposed by considering the instability of observations, three factors consisting of pseudorange, Doppler frequency, and carrier phase are added for the optimization estimation when the corresponding observation conditions are met. Lastly, the dynamic window optimization rules are designed according to the satellites distribution state, and the length of optimization window is adjusted to follow the change of GNSS blockage. The road tests show that the proposed method enhances more than 40% of positioning accuracy in the blockage interval compared to the conventional fusion method and improves positioning accuracy in urban canyons effectively.