Abstract
Recent results on joint detection—estimation for discrete data are extended to the continuous case for Gaussian signals in white Gaussian noise. Stochastic differential equations are obtained describing the temporal evolution of the sufficient statistic for the minimum Bayes' risk detection and the optimal mean-square error estimate of the signal state vector. An approximate solution for the estimation equation is presented and the results are extended to the case of multishot joint detection estimation.
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