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We characterize the invariant filtering measures resulting from Kalmanfiltering with intermittent observations (\cite{Bruno}), where the observationarrival is modeled as a Bernoulli process. In \cite{Riccati-weakconv}, it wasshown that there exists a $\overline{\gamma}^{\{\scriptsize{sb}}}>0$ such thatfor every observation packet arrival probability $\overline{\gamma}$,$\overline{\gamma}>\overline{\gamma}^{\{\scriptsize{sb}}}>0$, the sequence ofrandom conditional error covariance matrices converges in distribution to aunique invariant distribution $\mathbb{\mu}^{\overline{\gamma}}$ (independentof the filter initialization.) In this paper, we prove that, for controllableand observable systems, $\overline{\gamma}^{\{\scriptsize{sb}}}=0$ and that, as$\overline{\gamma}\uparrow 1$, the family$\{\mathbb{\mu}^{\overline{\gamma}}\}_{\overline{\gamma}>0}$ of invariantdistributions satisfies a moderate deviations principle (MDP) with a good ratefunction $I$. The rate function $I$ is explicitly identified. In particular,our results show:

Moderate Deviations of the Random Riccati Equation