The accuracy of prior information is a key element to ensure accuracy and reliability of the collaborative navigation system. The unknown and time-varying noise will be generated by external disturbances in a complex environment. To address this issue, a variational adaptive cooperative navigation method based on belief propagation is proposed. Firstly, based on the basic model of sigma point belief propagation (SPBP) cooperative navigation, the forward filtering process of cooperative navigation based on the confidence propagation mechanism is completed. The process noise and measurement noise are treated as the prior information of Bayesian estimation by IW (Inverse-Wishart). Then, the forward filtering value is used to establish a sliding window to smooth the noise variable to solve the filtering accuracy decline caused by the time variation of noise. Compared with that of the SPBP algorithm without smoothing operation, simulation results show that the position error of the slide window variational adaptive sigma point-belief propagation (SWSP) algorithm with smoothing operation is reduced by 90% due to the noise time-varying. The accuracy is much close to that of the opt SPBP algorithm.