Abstract: This paper presents an estimation of soil moisture based on Bayesian assimilation. Firstly, the backscattering coefficient and brightness temperature are measured by scatterometer and radiometer in the joint experiment. Then the Bayesian assimilation is utilized for the results from active and passive retrieval models. The assimilative results of the mean square error (MSE), mean absolute deviation (MAD) and mean relative error (MRE) are 3.56, 1.36, and 13.92% smaller than real value, respectively. Moreover, the coefficient of determination result of hierarchical Bayesian (HB) and classic Bayesian (CB) are 0.77 and 0.60, respectively, which prove that the Bayesian assimilation results are better than inverse model which based on single sensors during the growth season.