Convergence of discrete-time Kalman filter estimate to continuous-time estimate for systems with unbounded observation

TL;DR

This paper extends convergence results of discrete-time Kalman filter estimates to continuous-time estimates for systems with unbounded observation operators, providing bounds on convergence rates under various assumptions.

Contribution

It generalizes convergence results to systems with unbounded observation operators, including diagonalizable, admissible, and analytic semigroup systems.

Findings

Convergence of discrete-time Kalman filter to continuous-time estimate as discretization refines

Bounds established for the convergence rate of the variance discrepancy

Applicable to a broader class of systems with unbounded observation operators

Abstract

In this article, we complement recent results on the convergence of the state estimate obtained by applying the discrete-time Kalman filter on a time-sampled continuous-time system. As the temporal discretization is refined, the estimate converges to the continuous-time estimate given by the Kalman--Bucy filter. We shall give bounds for the convergence rates for the variance of the discrepancy between these two estimates. The contribution of this article is to generalize the convergence results to systems with unbounded observation operators under different sets of assumptions, including systems with diagonaliz-able generators, systems with admissible observation operators, and systems with analytic semigroups. The proofs are based on applying the discrete-time Kalman filter on a dense, numerable subset on the time interval [0,T] and bounding the increments obtained. These bounds are obtained by studying the regularity of the underlying semigroup and the noise-free output.