Aiming at the nonlinearity enhancement of the GNSS / SINS integrated navigation system in strong maneuvering vehicular environment and the accumulation of rounding errors as the iteration times increase, the covariance matrix is no longer non-negative, resulting in filtering accuracy decrease even filtering divergence, motion constraint aided integrated navigation method based on SVDCKF was proposed. To restrain the divergence of forward velocity errors and the decrease of position accuracy when sideslip occurs, the centripetal acceleration constraint is introduced based on the traditional motion constraint. In order to verify the effectiveness of the algorithm, a car experiment was carried out. Compared with the standard SVD-CKF, the results show that the longitude and latitude error of the proposed motion constraint aided SVD-CKF algorithm reduced by about 10. 54% and 44. 64% on average at the curve, the east and north velocity errors are reduced by about 50. 87% and 62. 61% on average. This algorithm not only ensures the position accuracy of the carrier in vehicular environment, but also improves the stability and robustness of the integrated navigation system.