Abstract
The solution to a continuous-time LQG minimax terminal state estimation problem is obtained using a Hilbert space approach. The minimax decision rule is determined via the method of least favourable prior distributions. The minimax estimator is shown to be a linear functional of the observed data, and the least favourable prior distribution is shown to be a degenerate Gaussian stochastic process.

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