DocumentCode :
2271425
Title :
Best linear unbiased estimator algorithm for received signal strength based localization
Author :
Lanxin Lin ; So, H.C.
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong, China
fYear :
2011
fDate :
Aug. 29 2011-Sept. 2 2011
Firstpage :
1989
Lastpage :
1993
Abstract :
Locating an unknown-position source using measurements from an array of spatially separated sensors with low complexity is quite necessary in many applications. In this paper, a linear least squares (LLS) method, which is a best linear unbiased estimator, is proposed to estimate the unknown-position source location based on the received signal strength (RSS) measurements. It is proved that the performance of our proposed method is identical to that of an existing LLS technique but the former is more computationally efficient. A relaxation method is also introduced to extend the LLS methods for RSS-based positioning with unknown path-loss factor. Furthermore, numerical examples are included to evaluate the performance of proposed algorithm by comparing with the existing LLS approach and their theoretical position variances as well as Cramér-Rao lower bound.
Keywords :
RSSI; least squares approximations; Cramér-Rao lower bound; LLS methods; RSS-based positioning; linear least squares method; linear unbiased estimator algorithm; path-loss factor; received signal strength based localization; spatially separated sensors; theoretical position variances; Covariance matrices; Estimation; Fading; Receivers; Signal processing algorithms; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2011 19th European
Conference_Location :
Barcelona
ISSN :
2076-1465
Type :
conf
Filename :
7074178
Link To Document :
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