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Optimized confidence weights for localization algorithms with scarce information

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2 Author(s)
Destino, G. ; Centre for Wireless Commun., Univ. of Oulu, Oulu ; de Abreu, G.T.F.

A method to derive weights to be used in distance-based multi-dimensional scaling (MDS) source localization algorithms under scarce information is discussed. In particular, a family of weighing function is derived with basis on small-scale statistics and the parameter that drives the choice of a particular weighing function out of such a family is optimized with basis on an information-theoretical criterion. It is found that, under the condition of scarce information, the proposed weighing strategy outperforms the alternative of utilizing an approximation of the maximum-likelihood (ML) weighing strategy.

Published in:

Ultra-Wideband, 2008. ICUWB 2008. IEEE International Conference on  (Volume:3 )

Date of Conference:

10-12 Sept. 2008

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