A recursive algorithm called 3-OM is presented to estimate parameters and noise variances for discrete-time linear stochastic systems. The unprojected version of 3-OM is globally convergent with probability 1 to minima of the asymptotic negative log-likelihood function. 3-OM approximates the quick convergence attained by the optimal nonlinear tilter used as a parameter estimator. The state-space form of 3-OM permits application to time-varying linear systems and to on-line tuning of a Karman filter.