We investigate the asymptotic properties of a recursive kernel density estimator of the driven noise of multivariate ARMAX models in adaptive tracking. We provide an almost sure pointwise and uniform strong law of large numbers as well as a pointwise and multivariate central limit theorem. We also carry out a goodness-of-fit test together with some simulation experiments.