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We consider the problem of estimator performance prediction in stochastic systems with Markov switching dynamical models. Following Hernandez et al, a new best-fitting Gaussian performance measure (BFG-PM) for jump Markov systems is proposed. The new BFG-PM matches the moments of the state transition density of the Markov switching system and the approximate uni-modal system. The new BFG-PM has a...
The problem is joint detection and tracking of possibly several objects moving through a region of interest. A wireless sensor network (WSN), deployed in the region, collects the acoustic energy measurements and sends them to the fusion center for processing. The problem is cast in the sequential Bayesian estimation framework and solved using a particle filter. The number of objects is unknown and...
Given an area where an unknown number of unaccounted radioactive sources potentially exist, and using gamma- radiation count measurements collected at known locations within this area, the problem is to estimate the number of sources as well as their locations and intensities. Two approaches are investigated. The first is based on the maximum likelihood estimation and the generalised maximum likelihood...
The problem is to localise a source of gamma radiation using dose rate measurements taken with a gamma probe at various points in space. A statistical model of dose-rate counts is developed using experimental data recorded in a laboratory. The problem is then studied using the theoretical Cramer-Rao bound (CRB) analysis, which quantifies the accuracy with which it is possible to localise the source...
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