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This paper deals with the problem of estimating the state of a discrete-time stochastic linear system based on data collected from multiple sensors with limited communication resources. For the cases of transmitting measurements and local state estimates, respectively, we design data-driven communication schemes based on a normalized innovation vector and corresponding fusion rules in the (approximate)...
Double sequential probability ratio test (2-SPRT), as an extended version of SPRT to cope with the no-upper-bound problem, is extended to the multiple-model hypothesis testing (MMHT) approach, called 2-MMSPRT, for detecting unknown events that may have multiple prior distributions. Not only does it address the mis-specified problem of the SPRT based MMHT method (MMSPRT), but it also can be expected...
This paper is concerned with state estimation of a linear system by fusion of asynchronous, multirate, multisensor data. The system is described at the finest scale with multiple sensors observing a common thing independently at different scales with different sampling rates. Unreliable measurements are available. The main results are: the multiscale system is properly formulated, a credibility measure...
Joint decision and estimation (JDE) is for solving problems involving inter-dependent decision and estimation and was proposed recently based on a generalized Bayes risk. The currently available JDE algorithm processes data in a batch manner. This batch method is computationally inefficient or infeasible for many dynamic JDE problems where measurements are made available sequentially. Therefore, this...
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