Brief paper: A separation theorem for stochastic control problems with point-process observations
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Hi-index | 754.84 |
In this correspondence, we examine the problem of estimating the centroid of a normally shaped intensity function of a time-space point process in terms of an observed realization of the point process. The centroid is assumed to move randomly as a projection of a Gauss-Markov process. We find that the centroid is conditionally normal given the observations. Dynamical equations are given for the conditional mean and covariance of the centroid. The resulting filter is nonlinear, but closely related to the continuous-discrete Kalman-Bucy filter. An application to optical position sensing is given.