This paper deals with the problem of adaptive estimation in the continuous time Kalman filtration scheme. The necessary and sufficient conditions of the convergence of the parameter estimators are discussed. For systems which are characterized by constant but unknown parameters, the conditions of convergence can be checked before the observation start. The method of proof is based on the relations between singularity property of some probability measures and convergence of the Bayesian estimation algorithm.