MAP moving horizon estimation for threshold measurements with application to field monitoring

20 Sep 2019 Battistelli Giorgio Chisci Luigi Forti Nicola Gherardini Stefano

The paper deals with state estimation of a spatially distributed system given noisy measurements from pointwise-in-time-and-space threshold sensors spread over the spatial domain of interest. A Maximum A posteriori Probability (MAP) approach is undertaken and a Moving Horizon (MH) approximation of the MAP cost-function is adopted... (read more)

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