BLOCK DIAGONALLY DOMINANT POSITIVE DEFINITE APPROXIMATE FILTERS AND SMOOTHERS Running title: BLOCK DIAGONALLY DOMINANT APPROXIMATE FILTERS Subtitle: Kalman filters and smoothers are approximated when the transition matrix and the incremental information are nearly block diagonal
نویسنده
چکیده
We examine stochastic dynamical systems where the transition matrix, Φ, and the system noise, ΓQΓ T , covariance are nearly block diagonal. When H TR−1H is also nearly block diagonal, where R is the observation noise covariance and H is the observation matrix, our suboptimal filter/smoothers are always positive semidefinite, and have improved numerical properties. Applications for distributed dynamical systems with time dependent pixel imaging are discussed.
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