DocumentCode :
2810418
Title :
Localization bias correction in n-dimensional space
Author :
Ji, Yiming ; Yu, Changbin ; Anderson, Brian D O
Author_Institution :
Res. Sch. of Inf. Sci. & Eng., Australian Nat. Univ., Canberra, ACT, Australia
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
2854
Lastpage :
2857
Abstract :
In previous work we proposed a method to determine the bias in localization algorithms using 2 or 3 sensors, whose location have been already identified, for targets in 2-dimensional space by mixing Taylor series and Jacobian matrices. In this paper we extend the bias-correction method to n-dimensional space with N sensors. To illustrate this approach, we analyze the proposed method in three situations using localization algorithms. Monte Carlo simulation results demonstrate the proposed bias-correction method can correct the bias very well in most situations.
Keywords :
Jacobian matrices; Monte Carlo methods; sensors; target tracking; Jacobian matrix; Monte Carlo simulation; Taylor series; bias correction method; n-dimensional space; Algebra; Algorithm design and analysis; Australia; Cost function; Jacobian matrices; Measurement errors; Noise measurement; Position measurement; Taylor series; Tensile stress; Bias correction; Localization; Sensor network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5496177
Filename :
5496177
Link To Document :
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