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- W2903468909 abstract "We consider the problem of RSSI-based self-localization by a resource-constrained mobile node given only a single perturbed observation of each RSSI measurement and inaccurate anchor positions. Most existing solutions assume additive independent zero-mean Gaussian perturbations in the observations. We consider a more realistic log-normal shadowing path-loss model for the radio propagation in which RSSI-based distance estimates follow log-normal distribution. We propose a bias-compensated pseudo-linear solution (PLS) using the weighted least-squares (WLS) method. The weights are estimated using the statistical properties of the perturbations in the RSSI-induced distance estimates and anchor position observations. The performance of PLS is evaluated over arbitrarily selected network geometries and compared with an existing WLS-based solution, which only accounts for the perturbations in the distance estimates. Simulation results show that PLS can substantially reduce the root-mean-square error and bias of the existing solution to almost half in many scenarios. (C) 2018 Elsevier B.V. All rights reserved." @default.
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- W2903468909 date "2019-01-01" @default.
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- W2903468909 title "Pseudo-linear localization using perturbed RSSI measurements and inaccurate anchor positions" @default.
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- W2903468909 doi "https://doi.org/10.1016/j.pmcj.2018.11.004" @default.
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