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• W2291495589 abstract "In this paper a multiple target localization problem is considered with only a partially known signal propagation model. Specifically, we assume that localization is to be effected by measuring the received signal strength (RSS) at each sensor. That RSS is modeled by a standard signal propagation model, though with unknown parameters. We adopt a Bayesian approach to propose a Markov Chain Monte Carlo (MCMC) type of algorithm for simultaneously estimating these unknown parameters and the source locations. Our approach also yields a posterior density function of these quantities conditioned on the RSS measurements. Such a density is useful for a visual inspection of the terrain to ascertain the source locations. The convergence of the algorithm is established under mild assumptions. Simulation results that support the analysis are provided." @default.
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• W2291495589 date "2015-12-01" @default.
• W2291495589 modified "2023-10-14" @default.
• W2291495589 title "A bayesian approach to multiple target localization" @default.
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• W2291495589 doi "https://doi.org/10.1109/cdc.2015.7402571" @default.
• W2291495589 hasPublicationYear "2015" @default.
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