Moderate Deviations of the Random Riccati Equation

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