In order to assess battlefield situation accurately and quickly ， an algorithm for online parameters learning is proposed on the basis of dynamitic Bayesian networks （ DBN ） . Forward recursion algorithm is used to estimate the parameters of network model after the structure model of dynamic Bayesian network is confirmed by expert knowledge. Dirichlet distribution is used as the prior distribution of samples according to the characteristics of small samples for the observation value of battlefield situation model ， and moment estimation is adopt to estimate the hyper parameters of the prior distribution. Then ， in combination with the equivalent samples value from the prior distribution ， the observation value can be used to implement parameters learning and battlefield situation assessment. Simulated results indicate that the proposed algorithm is of good real-time performance and high accuracy for situation assessment.