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The factor graph approach to discrete-time linear Gaussian state space modelsis well developed. The paper extends this approach to continuous-time linearsystems/filters that are driven by white Gaussian noise. By Gaussian messagepassing, we then obtain MAP/MMSE/LMMSE estimates of the input signal, or of thestate, or of the output signal from noisy observations of the output signal.These estimates may be obtained with arbitrary temporal resolution. Theproposed input signal estimation does not seem to have appeared in the priorKalman filtering literature.

LMMSE Estimation and Interpolation of Continuous-Time Signals from Discrete-Time Samples Using Factor Graphs