DocumentCode
2518448
Title
Analysis of linear least square solution for RSS based localization
Author
Salman, N. ; Guo, Y. Jay ; Kemp, A.H. ; Ghogho, M.
Author_Institution
Sch. of Electron. & Electr. Eng., Univ. of Leeds, Leeds, UK
fYear
2012
fDate
2-5 Oct. 2012
Firstpage
1051
Lastpage
1054
Abstract
Positioning of wireless devices has received a great deal of interest from researchers in the last decade. In order to locate nodes in low complexity and power efficient networks, the received signal strength (RSS) based positioning systems have been the center of focus. RSS based localization needs no additional hardware and hence is favored for low complexity and cheap localization networks. A major source of error in RSS location estimation is due to shadowing effects in multipath wireless channels. In this paper we analyze the performance of RSS location estimator based on the linear least square approach. We derive expressions for mean square error (MSE) and bias of location estimates. The theoretical analysis is compared with simulation results and it is observed that the analysis accurately predicts the performance of the location estimation. We also discuss the impact of reference node placement on estimation bias.
Keywords
least squares approximations; mean square error methods; mobility management (mobile radio); wireless channels; RSS based localization; RSS location estimator; linear least square approach; linear least square solution; localization network; location estimation; mean square error; multipath wireless channel; received signal strength; shadowing effect; wireless device positioning; Complexity theory; Equations; Estimation; Global Positioning System; Vectors; Wireless communication; Wireless sensor networks; Linear least square (LLS); Localization;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications and Information Technologies (ISCIT), 2012 International Symposium on
Conference_Location
Gold Coast, QLD
Print_ISBN
978-1-4673-1156-4
Electronic_ISBN
978-1-4673-1155-7
Type
conf
DOI
10.1109/ISCIT.2012.6380846
Filename
6380846
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