Bias-Correction In Localization Algorithms
Date
2009
Authors
Ji, Yiming
Yu, Changbin (Brad)
Anderson, Brian
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Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
In this paper we introduce a new approach to determine the bias in localization algorithms by mixing Taylor series and Jacobian matrices, which results in an easily calculated analytical expression for the bias. To illustrate this approach, we analyze the proposed method in two situations using localization algorithms based on distance measurements. Monte Carlo simulations verify that the proposed method is consistent with the performance of localization algorithms, which means the bias-correction method can correct the bias in most situations except when there is a collinearity problem. Although the method is analyzed in distance-based localization algorithms, it can be extended to other kinds of localization algorithms.
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Keywords
Keywords: Analytical expressions; Bias correction; Collinearity; Distance-based; Localization algorithm; Monte Carlo Simulation; New approaches; Computer simulation; Jacobian matrices; Monte Carlo methods; Sensor networks; Algorithms Bias correction; Localization; Sensor network
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Source
Proceedings of IEEE Global Communications Conference, Exhibition & Industry Forum (GLOBECOM 2009)
Type
Conference paper
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Restricted until
2037-12-31
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