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TOA-Based Source Localization: A Linearization Approach Adopting Coordinate System Translation
Author(s) -
Shunyuan Sun,
Shouhong Zhu,
Zhiguo Ding,
Baoguo Xu
Publication year - 2013
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2013/379369
Subject(s) - cramér–rao bound , linearization , computer science , estimator , upper and lower bounds , nonlinear system , time of arrival , algorithm , position (finance) , gaussian , signal (programming language) , coordinate system , translation (biology) , control theory (sociology) , estimation theory , artificial intelligence , telecommunications , mathematics , statistics , wireless , control (management) , mathematical analysis , physics , chemistry , biochemistry , quantum mechanics , programming language , finance , messenger rna , economics , gene
This paper addresses the localization of a timing signal source based on the time of arrival (TOA) measurements that are collected from nearby sensors that are position known and synchronized to each other. Generally speaking, for such TOA-based source localization, the corresponding observation equations contain nonlinear relationship between measurements and unknown parameters, which normally results in the nonexistence of any efficient unbiased estimator that attains the Cramer-Rao lower bound (CRLB). In this paper, we devise a new approach that utilizes linearization and adopts suitable coordinate system translation to eliminate nonlinearity from the converted observation equations. The performance analysis and simulation study conducted show that our proposed algorithm can achieve the CRLB when the zero-mean Gaussian and independent measurement errors are sufficiently small. © 2013 Shunyuan Sun et al.

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